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1
Işık, Leyla, e Arne Winterhof. "Maximum-Order Complexity and Correlation Measures". Cryptography 1, n. 1 (13 maggio 2017): 7. http://dx.doi.org/10.3390/cryptography1010007.
2
Chen, Zhixiong, Ana I. Gómez, Domingo Gómez-Pérez e Andrew Tirkel. "Correlation measure, linear complexity and maximum order complexity for families of binary sequences". Finite Fields and Their Applications 78 (febbraio 2022): 101977. http://dx.doi.org/10.1016/j.ffa.2021.101977.
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Sun, Zhimin, e Arne Winterhof. "On the Maximum Order Complexity of the Thue-Morse and Rudin-Shapiro Sequence". Uniform distribution theory 14, n. 2 (1 dicembre 2019): 33–42. http://dx.doi.org/10.2478/udt-2019-0012.
Abstract (sommario):
AbstractExpansion complexity and maximum order complexity are both finer measures of pseudorandomness than the linear complexity which is the most prominent quality measure for cryptographic sequences. The expected value of the Nth maximum order complexity is of order of magnitude log N whereas it is easy to find families of sequences with Nth expansion complexity exponential in log N. This might lead to the conjecture that the maximum order complexity is a finer measure than the expansion complexity. However, in this paper we provide two examples, the Thue-Morse sequence and the Rudin-Shapiro sequence with very small expansion complexity but very large maximum order complexity. More precisely, we prove explicit formulas for their N th maximum order complexity which are both of the largest possible order of magnitude N. We present the result on the Rudin-Shapiro sequence in a more general form as a formula for the maximum order complexity of certain pattern sequences.
4
Sun, Zhimin, Xiangyong Zeng e Da Lin. "On the Nth maximum order complexity and the expansion complexity of a Rudin-Shapiro-like sequence". Cryptography and Communications 12, n. 3 (13 settembre 2019): 415–26. http://dx.doi.org/10.1007/s12095-019-00396-0.
5
Popoli, Pierre. "On the Maximum Order Complexity of Thue–Morse and Rudin–Shapiro Sequences along Polynomial Values". Uniform distribution theory 15, n. 2 (1 dicembre 2020): 9–22. http://dx.doi.org/10.2478/udt-2020-0008.
Abstract (sommario):
Abstract Both the Thue–Morse and Rudin–Shapiro sequences are not suitable sequences for cryptography since their expansion complexity is small and their correlation measure of order 2 is large. These facts imply that these sequences are highly predictable despite the fact that they have a large maximum order complexity. Sun and Winterhof (2019) showed that the Thue–Morse sequence along squares keeps a large maximum order complexity. Since, by Christol’s theorem, the expansion complexity of this rarefied sequence is no longer bounded, this provides a potentially better candidate for cryptographic applications. Similar results are known for the Rudin–Shapiro sequence and more general pattern sequences. In this paper we generalize these results to any polynomial subsequence (instead of squares) and thereby answer an open problem of Sun and Winterhof. We conclude this paper by some open problems.
6
Channon, Alastair. "Maximum Individual Complexity is Indefinitely Scalable in Geb". Artificial Life 25, n. 2 (maggio 2019): 134–44. http://dx.doi.org/10.1162/artl_a_00285.
Abstract (sommario):
Geb was the first artificial life system to be classified as exhibiting open-ended evolutionary dynamics according to Bedau and Packard's evolutionary activity measures and is the only one to have been classified as such according to the enhanced version of that classification scheme. Its evolution is driven by biotic selection, that is (approximately), by natural selection rather than artificial selection. Whether or not Geb can generate an indefinite increase in maximum individual complexity is evaluated here by scaling two parameters: world length (which bounds population size) and the maximum number of neurons per individual. Maximum individual complexity is found to be asymptotically bounded when scaling either parameter alone. However, maximum individual complexity is found to be indefinitely scalable, to the extent evaluated so far (with run times in years and billions of reproductions per run), when scaling both world length and the maximum number of neurons per individual together. Further, maximum individual complexity is shown to scale logarithmically with (the lower of) maximum population size and maximum number of neurons per individual. This raises interesting questions and lines of thought about the feasibility of achieving complex results within open-ended evolutionary systems and how to improve on this order of complexity growth.
7
Cardone, Lorenzo, e Stefano Quer. "The Multi-Maximum and Quasi-Maximum Common Subgraph Problem". Computation 11, n. 4 (27 marzo 2023): 69. http://dx.doi.org/10.3390/computation11040069.
Abstract (sommario):
The Maximum Common Subgraph problem has been long proven NP-hard. Nevertheless, it has countless practical applications, and researchers are still searching for exact solutions and scalable heuristic approaches. Driven by applications in molecular science and cyber-security, we concentrate on the Maximum Common Subgraph among an indefinite number of graphs. We first extend a state-of-the-art branch-and-bound procedure working on two graphs to N graphs. Then, given the high computational cost of this approach, we trade off complexity for accuracy, and we propose a set of heuristics to approximate the exact solution for N graphs. We analyze sequential, parallel multi-core, and parallel-many core (GPU-based) approaches, exploiting several leveraging techniques to decrease the contention among threads, improve the workload balance of the different tasks, reduce the computation time, and increase the final result size. We also present several sorting heuristics to order the vertices of the graphs and the graphs themselves. We compare our algorithms with a state-of-the-art method on publicly available benchmark sets. On graph pairs, we are able to speed up the exact computation by a 2× factor, pruning the search space by more than 60%. On sets of more than two graphs, all exact solutions are extremely time-consuming and of a complex application in many real cases. On the contrary, our heuristics are far less expensive (as they show a lower-bound for the speed up of 10×), have a far better asymptotic complexity (with speed ups up to several orders of magnitude in our experiments), and obtain excellent approximations of the maximal solution with 98.5% of the nodes on average.
8
Zhang, Xinhe, Wenbo Lv e Haoran Tan. "Low-Complexity GSM Detection Based on Maximum Ratio Combining". Future Internet 14, n. 5 (23 maggio 2022): 159. http://dx.doi.org/10.3390/fi14050159.
Abstract (sommario):
Generalized spatial modulation (GSM) technology is an extension of spatial modulation (SM) technology, and one of its main advantages is to further improve band efficiency. However, the multiple active antennas for transmission also brings the demodulation difficulties at the receiver. To solve the problem of high computational complexity of the optimal maximum likelihood (ML) detection, two sub-optimal detection algorithms are proposed through reducing the number of transmit antenna combinations (TACs) detected at the receiver. One is the maximum ratio combining detection algorithm based on repetitive sorting strategy, termed as (MRC-RS), which uses MRC repetitive sorting strategy to select the most likely TACs in detection. The other is the maximum ratio combining detection algorithm, which is based on the iterative idea of the orthogonal matching pursuit, termed the MRC-MP algorithm. The MRC-MP algorithm reduces the number of TACs through finite iterations to reduce the computational complexity. For M-QAM constellation, a hard-limited maximum likelihood (HLML) detection algorithm is introduced to calculate the modulation symbol. For the M-PSK constellation, a low-complexity maximum likelihood (LCML) algorithm is introduced to calculate the modulation symbol. The computational complexity of these two algorithms for calculating the modulation symbol are independent of modulation order. The simulation results show that for GSM systems with a large number of TACs, the proposed two algorithms not only achieve almost the same bit error rate (BER) performance as the ML algorithm, but also can greatly reduce the computational complexity.
9
Ren, Dongping, Jianxi Guo e Xiaoli Hao. "Bayesian network variable elimination method optimal elimination order construction". ITM Web of Conferences 45 (2022): 01012. http://dx.doi.org/10.1051/itmconf/20224501012.
Abstract (sommario):
Variable Elimination (VE) is the most basic one of many Bayesian network inference algorithms. The speed and complexity of reasoning mainly depend on the order of elimination. Finding the optimal elimination order is a Nondeterministic Polynomial Hard (NP-Hard) problem, which is often solved by heuristic search in practice. In order to improve the speed of reasoning of the variable elimination method, the minimum, maximum potential, minimum missing edge and minimum added complexity search methods are studied. The Asian network is taken as an example to analyze and calculate the complexity and elimination of the above search method. Meta-order, through MATLAB R2018a, the above different search methods were constructed and reasoned separately. Finally, the performance of the four search methods was compared by inference time analysis. The experimental results show that the minimum increase complexity search method is better than other search methods, and the average time consuming is at least 0.012s, which can speed up the reasoning process of Bayesian network.
10
He, Zai-Yin, Abderrahmane Abbes, Hadi Jahanshahi, Naif D. Alotaibi e Ye Wang. "Fractional-Order Discrete-Time SIR Epidemic Model with Vaccination: Chaos and Complexity". Mathematics 10, n. 2 (6 gennaio 2022): 165. http://dx.doi.org/10.3390/math10020165.
Abstract (sommario):
This research presents a new fractional-order discrete-time susceptible-infected-recovered (SIR) epidemic model with vaccination. The dynamical behavior of the suggested model is examined analytically and numerically. Through using phase attractors, bifurcation diagrams, maximum Lyapunov exponent and the 0−1 test, it is verified that the newly introduced fractional discrete SIR epidemic model vaccination with both commensurate and incommensurate fractional orders has chaotic behavior. The discrete fractional model gives more complex dynamics for incommensurate fractional orders compared to commensurate fractional orders. The reasonable range of commensurate fractional orders is between γ = 0.8712 and γ = 1, while the reasonable range of incommensurate fractional orders is between γ2 = 0.77 and γ2 = 1. Furthermore, the complexity analysis is performed using approximate entropy (ApEn) and C0 complexity to confirm the existence of chaos. Finally, simulations were carried out on MATLAB to verify the efficacy of the given findings.
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Shao, Z. Y., S. W. Cheung e T. I. Yuk. "Comparison of Semidefinite Relaxation Detectors for High-Order Modulation MIMO Systems". International Journal of Antennas and Propagation 2014 (2014): 1–8. http://dx.doi.org/10.1155/2014/614876.
Abstract (sommario):
Multiple-input multiple-output (MIMO) system is considered to be one of the key technologies of LTE since it achieves requirements of high throughput and spectral efficiency. The semidefinite relaxation (SDR) detection for MIMO systems is an attractive alternative to the optimum maximum likelihood (ML) decoding because it is very computationally efficient. We propose a new SDR detector for 256-QAM MIMO system and compare its performance with two other SDR detectors, namely, BC-SDR detector and VA-SDR detector. The tightness and complexity of these three SDR detectors are analyzed. Both theoretical analysis and simulation results demonstrate that the proposed SDR can provide the best BLER performance among the three detectors, while the BC-SDR detector and the VA-SDR detector provide identical BLER performance. Moreover, the BC-SDR has the lowest computational complexity and the VA-SDR has the highest computational complexity, while the proposed SDR is in between.
12
Chashkin, Aleksandr V. "On the average-case complexity of underdetermined functions". Discrete Mathematics and Applications 28, n. 4 (28 agosto 2018): 201–21. http://dx.doi.org/10.1515/dma-2018-0019.
Abstract (sommario):
Abstract The average-case complexity of computation of underdetermined functions by straight-line programs with conditional stop over the basis of all at most two-place Boolean functions is considered. Correct order estimates of the average-case complexity of functions with maximum average-case complexity among all underdetermined functions are derived depending on the degree of their determinacy, the size of their domain, and the size of their support.
13
Olsen, Valdemar Kargård, Jonathan R. Whitlock e Yasser Roudi. "The quality and complexity of pairwise maximum entropy models for large cortical populations". PLOS Computational Biology 20, n. 5 (2 maggio 2024): e1012074. http://dx.doi.org/10.1371/journal.pcbi.1012074.
Abstract (sommario):
We investigate the ability of the pairwise maximum entropy (PME) model to describe the spiking activity of large populations of neurons recorded from the visual, auditory, motor, and somatosensory cortices. To quantify this performance, we use (1) Kullback-Leibler (KL) divergences, (2) the extent to which the pairwise model predicts third-order correlations, and (3) its ability to predict the probability that multiple neurons are simultaneously active. We compare these with the performance of a model with independent neurons and study the relationship between the different performance measures, while varying the population size, mean firing rate of the chosen population, and the bin size used for binarizing the data. We confirm the previously reported excellent performance of the PME model for small population sizes N < 20. But we also find that larger mean firing rates and bin sizes generally decreases performance. The performance for larger populations were generally not as good. For large populations, pairwise models may be good in terms of predicting third-order correlations and the probability of multiple neurons being active, but still significantly worse than small populations in terms of their improvement over the independent model in KL-divergence. We show that these results are independent of the cortical area and of whether approximate methods or Boltzmann learning are used for inferring the pairwise couplings. We compared the scaling of the inferred couplings with N and find it to be well explained by the Sherrington-Kirkpatrick (SK) model, whose strong coupling regime shows a complex phase with many metastable states. We find that, up to the maximum population size studied here, the fitted PME model remains outside its complex phase. However, the standard deviation of the couplings compared to their mean increases, and the model gets closer to the boundary of the complex phase as the population size grows.
14
He, Yingjin, Jun Peng e Song Zheng. "Fractional-Order Financial System and Fixed-Time Synchronization". Fractal and Fractional 6, n. 9 (10 settembre 2022): 507. http://dx.doi.org/10.3390/fractalfract6090507.
Abstract (sommario):
This study is concerned with the dynamic investigation and fixed-time synchronization of a fractional-order financial system with the Caputo derivative. The rich dynamic behaviors of the fractional-order financial system with variations of fractional orders and parameters are discussed analytically and numerically. Through using phase portraits, bifurcation diagrams, maximum Lyapunov exponent diagrams, 0–1 testing and time series, it is found that chaos exists in the proposed fractional-order financial system. Additionally, a complexity analysis is carried out utilizing approximation entropy SE and C0 complexity to detect whether chaos exists. Furthermore, a synchronization controller and an adaptive parameter update law are designed to synchronize two fractional-order chaotic financial systems and identify the unknown parameters in fixed time simultaneously. The estimate of the setting time of synchronization depends on the parameters of the designed controller and adaptive parameter update law, rather than on the initial conditions. Numerical simulations show the effectiveness of the theoretical results obtained.
15
Sun, Zhimin, e Arne Winterhof. "On the maximum order complexity of subsequences of the Thue–Morse and Rudin–Shapiro sequence along squares". International Journal of Computer Mathematics: Computer Systems Theory 4, n. 1 (2 gennaio 2019): 30–36. http://dx.doi.org/10.1080/23799927.2019.1566275.
16
He, Yingjin, Song Zheng e Liguo Yuan. "Dynamics of Fractional-Order Digital Manufacturing Supply Chain System and Its Control and Synchronization". Fractal and Fractional 5, n. 3 (17 settembre 2021): 128. http://dx.doi.org/10.3390/fractalfract5030128.
Abstract (sommario):
Digital manufacturing is widely used in the production of automobiles and aircrafts, and plays a profound role in the whole supply chain. Due to the long memory property of demand, production, and stocks, a fractional-order digital manufacturing supply chain system can describe their dynamics more precisely. In addition, their control and synchronization may have potential applications in the management of real-word supply chain systems to control uncertainties that occur within it. In this paper, a fractional-order digital manufacturing supply chain system is proposed and solved by the Adomian decomposition method (ADM). Dynamical characteristics of this system are studied by using a phase portrait, bifurcation diagram, and a maximum Lyapunov exponent diagram. The complexity of the system is also investigated by means of SE complexity and C0 complexity. It is shown that the complexity results are consistent with the bifurcation diagrams, indicating that the complexity can reflect the dynamical properties of the system. Meanwhile, the importance of the fractional-order derivative in the modeling of the system is shown. Moreover, to further investigate the dynamics of the fractional-order supply chain system, we design the feedback controllers to control the chaotic supply chain system and synchronize two supply chain systems, respectively. Numerical simulations illustrate the effectiveness and applicability of the proposed methods.
17
Mikhailovsky, George. "Structuredness as a Measure of the Complexity of the Structure and the Role of Post-Dissipative Structures and Ratchet Processes in Evolution". Journal of Evolutionary Science 1, n. 2 (23 gennaio 2020): 40–52. http://dx.doi.org/10.14302/issn.2689-4602.jes-19-3155.
Abstract (sommario):
As shown earlier, the algorithmic complexity, like Shannon information and Boltzmann entropy, tends to increase in accordance with the general law of complification. However, the algorithmic complexity of most material systems does not reach its maximum, i.e. chaotic state, due to the various laws of nature that create certain structures. The complexity of such structures is very different from the algorithmic complexity, and we intuitively feel that its maximal value should be somewhere between order and chaos. I propose a formula for calculation such structural complexity, which can be called - structuredness. The structuredness of any material system is determined by structures of three main types: stable, dissipative, and post-dissipative. The latter are defined as stable structures created by dissipative ones, directly or indirectly. Post-dissipative structures, as well as stable, can exist for an unlimited time, but at the micro level only, without energy influx. The appearance of such structures leads to the “ratchet” process, which determines the structure genesis in non-living and, especially, in living systems. This process allows systems with post-dissipative structures to develop in the direction of maximum structuring due to the gradual accumulation of these structures, even when such structuring contradicts the general law of complification.
18
Liu, Li, Jin Kuan Wang, Xin Song, Ying Hua Han e Dong Mei Yan. "Sorted QR-Decomposition Based Parallel Detection Algorithm for MIMO Systems". Applied Mechanics and Materials 427-429 (settembre 2013): 591–95. http://dx.doi.org/10.4028/www.scientific.net/amm.427-429.591.
Abstract (sommario):
Multiple input multiple output (MIMO) wireless communication system can increase system capacity enormously. Maximum likelihood (ML) detection algorithm can obtain the optimal detection performance with exponential computational complexity that results it difficulty to use in practice. Classical ordered successive interference cancellation (SIC) algorithm suffers from error propagation and high complexity, so an improved parallel SIC algorithm based on Maximum likelihood (ML) detection is proposed, in which signal detection is performed at two stages. ML detections for one layer is carried out firstly, and redundancy of candidate sequences are selected to perform parallel detection for improving detection performance for next step. Sorted QR decomposition based SIC algorithm are performed in second step in order to reduce calculating complexity. By adjusting the number of candidate sequences, tradeoff between detection performance and calculating complexity can be obtained properly.
19
BENZINGER, RALPH. "Automated complexity analysis of Nuprl extracted programs". Journal of Functional Programming 11, n. 1 (gennaio 2001): 3–31. http://dx.doi.org/10.1017/s0956796800003865.
Abstract (sommario):
This paper describes the Automated Complexity Analysis Prototype (ACAp) system for automated complexity analysis of functional programs synthesized with the Nuprl proof development system. We define a simple abstract cost model for NUPRL's term language based on the current call-by-name evaluator. The framework uses abstract functions and abstract lists to facilitate reasoning about primitive recursive programs with first-order functions, lazy lists and a subclass of higher-order functions. The ACAp system automatically derives upper bounds on the time complexity of NUPRL extracts relative to a given profiling semantics. Analysis proceeds by abstract interpretation of the extract, where symbolic evaluation rules extend standard evaluation to terms with free variables. Symbolic evaluation of recursive programs generates systems of multi-variable difference equations, which are solved using the MATHEMATICA computer algebra system. The use of the system is exemplified by analyzing a proof extract that computes the maximum segment sum of a list and a functional program that determines the minimum of a list via sorting. For both results, we compare call-by-name to call-by-value evaluation.
20
Fassois, S. D., K. F. Eman e S. M. Wu. "A Suboptimum Maximum Likelihood Approach to Parametric Signal Analysis". Journal of Dynamic Systems, Measurement, and Control 111, n. 2 (1 giugno 1989): 153–59. http://dx.doi.org/10.1115/1.3153031.
Abstract (sommario):
A computationally efficient approach to stochastic ARMA modeling of wide-sense stationary signals is proposed. The discrete estimator minimizes a modified version of the likelihood function by using exclusively linear techniques, and thus circumventing the high computational complexity of the Maximum Likelihood (ML) method. The proposed approach is thus easy to implement, requires no explicit second order statistical information, and is shown to produce high quality estimates at a very modest computational cost. A recursive version of the algorithm, suitable for on-line implementation, is also developed, and, modeling strategy issues discussed. The effectiveness of the proposed approach is finally established through numerical simulations and comparisons with other suboptimum schemes.
21
BAE, SUNG EUN, e TADAO TAKAOKA. "ALGORITHMS FOR K-DISJOINT MAXIMUM SUBARRAYS". International Journal of Foundations of Computer Science 18, n. 02 (aprile 2007): 319–39. http://dx.doi.org/10.1142/s012905410700470x.
Abstract (sommario):
The maximum subarray problem is to find the array portion that maximizes the sum of array elements in it. For K disjoint maximum subarrays, Ruzzo and Tompa gave an O(n) time solution for one-dimension. This solution is, however, difficult to extend to two-dimensions. While a trivial solution of O(Kn3) time is easily obtainable for a two-dimensional array of size n × n, little study has been undertaken to improve the time complexity. We first propose an O(n + K log K) time solution for one-dimension. This is asymptotically equivalent to Ruzzo and Tompa's when sorted order is needed. Based on this, we achieve O(n3 + Kn2 log n) time for two-dimensions. This is cubic time when K ≤ n/ log n. We also show that this upper bound does not exceed O(n3 log n) for K > n, namely O(n3 + min (K,n) · n log n).
22
Hamadneh, Tareq, Abderrahmane Abbes, Ibraheem Abu Falahah, Yazan Alaya AL-Khassawneh, Ahmed Salem Heilat, Abdallah Al-Husban e Adel Ouannas. "Complexity and Chaos Analysis for Two-Dimensional Discrete-Time Predator–Prey Leslie–Gower Model with Fractional Orders". Axioms 12, n. 6 (6 giugno 2023): 561. http://dx.doi.org/10.3390/axioms12060561.
Abstract (sommario):
The paper introduces a novel two-dimensional fractional discrete-time predator–prey Leslie–Gower model with an Allee effect on the predator population. The model’s nonlinear dynamics are explored using various numerical techniques, including phase portraits, bifurcations and maximum Lyapunov exponent, with consideration given to both commensurate and incommensurate fractional orders. These techniques reveal that the fractional-order predator–prey Leslie–Gower model exhibits intricate and diverse dynamical characteristics, including stable trajectories, periodic motion, and chaotic attractors, which are affected by the variance of the system parameters, the commensurate fractional order, and the incommensurate fractional order. Finally, we employ the 0–1 method, the approximate entropy test and the C0 algorithm to measure complexity and confirm chaos in the proposed system.
23
Charles-Darby, Karel, Roberto Carrasco-Alvarez e R. Parra-Michel. "Complexity Reduction of MLSE and MAP Equalizers Using Modified Prolate Basis Expansion". Electronics 8, n. 11 (12 novembre 2019): 1333. http://dx.doi.org/10.3390/electronics8111333.
Abstract (sommario):
Maximum likelihood sequence estimation (MLSE) and maximum a posteriori probability (MAP) equalizers are optimum receivers for dealing with intersymbol interference (ISI) in time-dispersive channels. However, their high complexity and latency limit their widespread implementation; therefore, research into reducing their complexity is an open topic. This paper proposes a novel modification to reduce the computational complexity of the aforementioned algorithms, which exploits the representation of the communication channels in a time-delay-domain basis expansion model (BEM). It is shown that an appropriate basis is a set of modified prolate functions, in which the transmitter and receiver filters are considered in the kernel construction. Simulation results show that a reduction in sums and multiplications on the order of 55% can be obtained, maintaining the same bit error rate performance as in the traditional implementation.
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Hu, Feng, Kuo Tian e Zi-Ke Zhang. "Identifying Vital Nodes in Hypergraphs Based on Von Neumann Entropy". Entropy 25, n. 9 (25 agosto 2023): 1263. http://dx.doi.org/10.3390/e25091263.
Abstract (sommario):
Hypergraphs have become an accurate and natural expression of high-order coupling relationships in complex systems. However, applying high-order information from networks to vital node identification tasks still poses significant challenges. This paper proposes a von Neumann entropy-based hypergraph vital node identification method (HVC) that integrates high-order information as well as its optimized version (semi-SAVC). HVC is based on the high-order line graph structure of hypergraphs and measures changes in network complexity using von Neumann entropy. It integrates s-line graph information to quantify node importance in the hypergraph by mapping hyperedges to nodes. In contrast, semi-SAVC uses a quadratic approximation of von Neumann entropy to measure network complexity and considers only half of the maximum order of the hypergraph’s s-line graph to balance accuracy and efficiency. Compared to the baseline methods of hyperdegree centrality, closeness centrality, vector centrality, and sub-hypergraph centrality, the new methods demonstrated superior identification of vital nodes that promote the maximum influence and maintain network connectivity in empirical hypergraph data, considering the influence and robustness factors. The correlation and monotonicity of the identification results were quantitatively analyzed and comprehensive experimental results demonstrate the superiority of the new methods. At the same time, a key non-trivial phenomenon was discovered: influence does not increase linearly as the s-line graph orders increase. We call this the saturation effect of high-order line graph information in hypergraph node identification. When the order reaches its saturation value, the addition of high-order information often acts as noise and affects propagation.
25
Cercel, George, Cosmin Tigănaşu e Ciprian Nemeş. "Photovoltaic Systems Maximum Power Point Tracking Algorithms". Bulletin of the Polytechnic Institute of Iași. Electrical Engineering, Power Engineering, Electronics Section 67, n. 2 (1 giugno 2021): 19–29. http://dx.doi.org/10.2478/bipie-2021-0008.
Abstract (sommario):
Abstract The power delivered by a photovoltaic cell generator depends on the operating point at which this works. In order to maximize the energy supplied by the PV system, the generator should be adapted to the load so that the operating point will always correspond to the maximum power point. Usually, when a PV module is connected directly to a load, its operating point is rarely at the maximum power point. The operating principle of the maximum power point tracking is to place a converter between the load and the PV array, to adjust the output voltage and the current of the PV array so that the maximum available power is extracted. In most cases the optimal algorithm is chosen according to several criteria, such as: implementation complexity (autonomy of the systems, connected to the network), the type and number of sensors needed, the ability of the algorithm to detect local maximum points, cost, response time, type of implementation (analog, digital, mixed).
26
Nuñez-Perez, Jose-Cruz, Vincent-Ademola Adeyemi, Yuma Sandoval-Ibarra, Francisco-Javier Perez-Pinal e Esteban Tlelo-Cuautle. "Maximizing the Chaotic Behavior of Fractional Order Chen System by Evolutionary Algorithms". Mathematics 9, n. 11 (25 maggio 2021): 1194. http://dx.doi.org/10.3390/math9111194.
Abstract (sommario):
This paper presents the application of three optimization algorithms to increase the chaotic behavior of the fractional order chaotic Chen system. This is achieved by optimizing the maximum Lyapunov exponent (MLE). The applied optimization techniques are evolutionary algorithms (EAs), namely: differential evolution (DE), particle swarm optimization (PSO), and invasive weed optimization (IWO). In each algorithm, the optimization process is performed using 100 individuals and generations from 50 to 500, with a step of 50, which makes a total of ten independent runs. The results show that the optimized fractional order chaotic Chen systems have higher maximum Lyapunov exponents than the non-optimized system, with the DE giving the highest MLE. Additionally, the results indicate that the chaotic behavior of the fractional order Chen system is multifaceted with respect to the parameter and fractional order values. The dynamical behavior and complexity of the optimized systems are verified using properties, such as bifurcation, LE spectrum, equilibrium point, eigenvalue, and sample entropy. Moreover, the optimized systems are compared with a hyper-chaotic Chen system on the basis of their prediction times. The results show that the optimized systems have a shorter prediction time than the hyper-chaotic system. The optimized results are suitable for developing a secure communication system and a random number generator. Finally, the Halstead parameters measure the complexity of the three optimization algorithms that were implemented in MATLAB. The results reveal that the invasive weed optimization has the simplest implementation.
27
Ba, Bin, Weijia Cui, Daming Wang e Jianhui Wang. "Maximum Likelihood Time Delay Estimation Based on Monte Carlo Importance Sampling in Multipath Environment". International Journal of Antennas and Propagation 2017 (2017): 1–7. http://dx.doi.org/10.1155/2017/4215293.
Abstract (sommario):
In multipath environment, the computation complexity of single snapshot maximum likelihood for time delay estimation is huge. In particular, the computational complexity of grid search method increases exponentially with the increase of dimension. For this reason, this paper presents a maximum likelihood estimation algorithm based on Monte Carlo importance sampling technique. Firstly, the algorithm takes advantage of the channel frequency response in order to build the likelihood function of time delay in multipath environment. The pseudoprobability density function is constructed by using exponential likelihood function. Then, it is crucial to choose the importance function. According to the characteristic of the Vandermonde matrix in likelihood function, the product of the conjugate transpose Vandermonde matrix and itself is approximated by the product of a constant and an identity matrix. The pseudoprobability density function can be decomposed into product of many probability density functions of single path time delay. The importance function is constructed. Finally, according to probability density function of multipath time delay decomposed by importance function, the time delay of the multipath is sampled by Monte Carlo method. The time delay is estimated via calculating weighted mean of sample. Simulation results show that the performance of proposed algorithm approaches the Cramér-Rao bound with reduced complexity.
28
Adeyemi, Vincent-Ademola, Esteban Tlelo-Cuautle, Francisco-Javier Perez-Pinal e Jose-Cruz Nuñez-Perez. "Optimizing the Maximum Lyapunov Exponent of Fractional Order Chaotic Spherical System by Evolutionary Algorithms". Fractal and Fractional 6, n. 8 (18 agosto 2022): 448. http://dx.doi.org/10.3390/fractalfract6080448.
Abstract (sommario):
The main goal of this work is to optimize the chaotic behavior of a three-dimensional chaotic-spherical-attractor-generating fractional-order system and compare the results with its novel hyperchaotic counterpart. The fractional-order chaotic system is a smooth system perturbed with a hyperbolic tangent function. There are two major contributions in this investigation. First, the maximum Lyapunov exponent of the chaotic system was optimized by applying evolutionary algorithms, which are meta-heuristics search algorithms, namely, the differential evolution, particle swarm optimization, and invasive weed optimization. Each of the algorithms was populated with one hundred individuals, the maximum generation was five hundred, and the total number of design variables was eleven. The results show a massive increase of over 5000% in the value of the maximum Lyapunov exponent, thereby leading to an increase in the chaotic behavior of the system. Second, a hyperchaotic system of four dimensions was constructed from the inital chaotic system. The dynamics of the optimized chaotic and the new hyperchaotic systems were analyzed using phase portraits, time series, bifurcation diagrams, and Lyapunov exponent spectra. Finally, comparison between the optimized chaotic systems and the hyperchaotic states shows an evidence of more complexity, ergodicity, internal randomness, and unpredictability in the optimized systems than its hyperchaotic counterpart according to the analysis of their information entropies and prediction times.
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MA, HONG, JIE ZHOU, LI MA e YUAN Y. TANG. "ORDER STATISTIC FILTER (OSF): A NOVEL APPROACH TO DOCUMENT ANALYSIS". International Journal of Pattern Recognition and Artificial Intelligence 16, n. 05 (agosto 2002): 551–71. http://dx.doi.org/10.1142/s0218001402001873.
Abstract (sommario):
Page segmentation is one of the important and basic research subjects of document analysis. There are two major kinds of page segmentation methods, i.e. hierarchical and no-hierarchical ones. Most traditional techniques such as top–down and bottom–up approaches belong to the hierarchical method. Though these two approaches have been used till now, they are not effective for processing documents with high geometric complexity and the process of splitting document needs iterative operations which is time consuming. A non-hierarchical method called the modified fractal signature (MFS) was presented in recent years. It can overcome the above weaknesses, however the MFS needs to calculate modified fractal signature which makes the theory very complex. In this thesis, we present a new page segmentation approach: Median Order Statistic Filter (MedOSF) — Maximum Order Statistic Filter (MaxOSF) approach which is more direct and much simpler. We use the MedOSF to remove the salt–pepper noise of the document and use the MaxOSF to do the page segmentation. In practice, they not only can adaptively process the documents with high geometrical complexity, but also save a lot of computing time.
30
Zhao, Yang, Jianxin Wu, Zhiyong Suo e Xiaoyu Liu. "Fast Implementation of Approximated Maximum Likelihood Parameter Estimation for Frequency Agile Radar under Jamming Environment". Sensors 20, n. 7 (3 aprile 2020): 2022. http://dx.doi.org/10.3390/s20072022.
Abstract (sommario):
A computationally efficient target parameter estimation algorithm for frequency agile radar (FAR) under jamming environment is developed. First, the barrage noise jamming and the deceptive jamming are suppressed by using adaptive beamforming and frequency agility. Second, the analytical solution of the parameter estimation is obtained by a low-order approximation to the multi-dimensional maximum likelihood (ML) function. Due to that, fine grid-search (FGS) is avoided and the computational complexity is greatly reduced.
31
Jing, Xiaorong, Mingyue Wang, Wei Zhou e Hongqing Liu. "Improved QRD-M Detection Algorithm for Generalized Spatial Modulation Scheme". International Journal of Antennas and Propagation 2017 (2017): 1–9. http://dx.doi.org/10.1155/2017/3581592.
Abstract (sommario):
Generalized spatial modulation (GSM) is a spectral and energy efficient multiple-input multiple-output (MIMO) transmission scheme. It will lead to imperfect detection performance with relatively high computational complexity by directly applying the original QR-decomposition with M algorithm (QRD-M) to the GSM scheme. In this paper an improved QRD-M algorithm is proposed for GSM signal detection, which achieves near-optimal performance but with relatively low complexity. Based on the QRD, the improved algorithm firstly transforms the maximum likelihood (ML) detection of the GSM signals into searching an inverted tree structure. Then, in the searching process of the M branches, the branches corresponding to the illegitimate transmit antenna combinations (TACs) and related to invalid number of active antennas are cut in order to improve the validity of the resultant branches at each level by taking advantage of characteristics of GSM signals. Simulation results show that the improved QRD-M detection algorithm provides similar performance to maximum likelihood (ML) with the reduced computational complexity compared to the original QRD-M algorithm, and the optimal value of parameter M of the improved QRD-M algorithm for detection of the GSM scheme is equal to modulation order plus one.
32
Ayrulu-Erdem, Birsel, e Billur Barshan. "Leg Motion Classification with Artificial Neural Networks Using Wavelet-Based Features of Gyroscope Signals". Sensors 11, n. 2 (28 gennaio 2011): 1721–43. http://dx.doi.org/10.3390/s110201721.
Abstract (sommario):
We extract the informative features of gyroscope signals using the discrete wavelet transform (DWT) decomposition and provide them as input to multi-layer feed-forward artificial neural networks (ANNs) for leg motion classification. Since the DWT is based on correlating the analyzed signal with a prototype wavelet function, selection of the wavelet type can influence the performance of wavelet-based applications significantly. We also investigate the effect of selecting different wavelet families on classification accuracy and ANN complexity and provide a comparison between them. The maximum classification accuracy of 97.7% is achieved with the Daubechies wavelet of order 16 and the reverse bi-orthogonal (RBO) wavelet of order 3.1, both with similar ANN complexity. However, the RBO 3.1 wavelet is preferable because of its lower computational complexity in the DWTdecomposition and reconstruction.
33
Chen, Jiming, Shamik Ghosh e Wen Zhao. "Scalar Quadratic Maximum-likelihood Estimators for the CMB Cross-power Spectrum". Astrophysical Journal Supplement Series 260, n. 2 (1 giugno 2022): 44. http://dx.doi.org/10.3847/1538-4365/ac679f.
Abstract (sommario):
Abstract Estimating the cross-correlation power spectra of the cosmic microwave background, in particular, the TB and EB spectra, is important for testing parity symmetry in cosmology and diagnosing insidious instrumental systematics. The quadratic maximum-likelihood (QML) estimator provides optimal estimates of the power spectra, but it is computationally very expensive. The hybrid pseudo-C ℓ estimator is computationally fast but performs poorly on large scales. As a natural extension of previous work, in this article, we present a new unbiased estimator based on the Smith–Zaldarriaga (SZ) approach of E–B separation and the scalar QML approach to reconstruct the cross-correlation power spectrum, called the QML-SZ estimator. Our new estimator relies on the ability to construct scalar maps, which allows us to use a scalar QML estimator to obtain the cross-correlation power spectrum. By reducing the pixel number and algorithm complexity, the computational cost is nearly one order of magnitude smaller and the running time is nearly two orders of magnitude faster in the test situations.
34
Gîrbacia, Teodora, e Gheorghe Mogan. "An Improvement of the Rapidly-Exploring Random Tree Method for Path Planning of a Car-Like Robot in Virtual Environment". Applied Mechanics and Materials 772 (luglio 2015): 471–76. http://dx.doi.org/10.4028/www.scientific.net/amm.772.471.
Abstract (sommario):
In this paper we present a method of reducing the computational complexity necessary in path planning for a car-like robot in order to generate the optimal path according to the constrains set by the user. The proposed method implies adding the following constrains: setting the maximum and minimum distance between the possible paths and the obstacles placed in the virtual environment in order to reduce the simulation time and to obtain a real-time application and to remove the paths that contain unnecessary turns around the environment without avoiding an obstacle. By applying this method the simulation complexity is reduced and the optimal path is easier to find.
35
Cohen, Gil, e Mahmoud Qadan. "The Complexity of Cryptocurrencies Algorithmic Trading". Mathematics 10, n. 12 (12 giugno 2022): 2037. http://dx.doi.org/10.3390/math10122037.
Abstract (sommario):
In this research, we provided an answer to a very important trading question, what is the optimal number of technical tools in order to achieve the best trading results for both swing trade that uses daily bars and intraday trade that uses minutes bars? We designed Machine Learning (ML) systems that can trade four major cryptocurrencies: Bitcoin, Ethereum, BNB, and Solana. We found that more indicators do not necessarily mean better trading performance. Swing traders that use daily bars should trade Bitcoin and Solana using Ichimoku Cloud (IC) plus Moving Average Convergence Divergence (MACD), Ethereum with IC plus Chaikin Money Flow (CMF), and BNB with IC alone. With regard to intraday trading, we documented that different cryptocurrencies should be trading using different time frames. These results emphasize that the optimal number of indicators that are used to trade daily bars is one or, at maximum, two. The Multi-Layer (MUL) system that consists of all three examined technical indicators failed to improve the trading results for both days (swing) and intraday trades. The main implication of this study for traders is that more indicators does not necessarily improve trades performances.
36
Zhang, Jie, Dehui Wang, Kai Yang e Xiaogang Dong. "First-Order Random Coefficient Multinomial Autoregressive Model for Finite-Range Time Series of Counts". Symmetry 13, n. 12 (29 novembre 2021): 2271. http://dx.doi.org/10.3390/sym13122271.
Abstract (sommario):
In view of the complexity and asymmetry of finite range multi-state integer-valued time series data, we propose a first-order random coefficient multinomial autoregressive model in this paper. Basic probabilistic and statistical properties of the model are discussed. Conditional least squares (CLS) and weighted conditional least squares (WCLS) estimators of the model parameters are derived, and their asymptotic properties are established. In simulation studies, we compare these two methods with the conditional maximum likelihood (CML) method to verify the proposed procedure. A real example is applied to illustrate the advantages of our model.
37
Boglietti, Aldo, Fabio Mandrile, Enrico Carpaneto, Mircea Popescu, Sandro Rubino e David Staton. "Stator Winding Second-Order Thermal Model including End-Winding Thermal Effects". Energies 14, n. 20 (13 ottobre 2021): 6578. http://dx.doi.org/10.3390/en14206578.
Abstract (sommario):
This paper proposes a second-order thermal model for electrical machines. The goal of this model is the prediction of the average winding temperature during short and long thermal transients up to the steady-state conditions. First, the thermal parameters of the electrical machine are determined by a DC test. Then, the proposed model is characterized and validated using AC tests. The accuracy of the proposed thermal model has been verified comparing the computed temperatures with the measured ones. The maximum error found during the thermal transient is lower than 3%, an excellent result comparing the complexity of a total enclosed fan cooled induction motor and the simplicity of the proposed model.
38
Boglietti, Aldo, Fabio Mandrile, Enrico Carpaneto, Mircea Popescu, Sandro Rubino e David Staton. "Stator Winding Second-Order Thermal Model including End-Winding Thermal Effects". Energies 14, n. 20 (13 ottobre 2021): 6578. http://dx.doi.org/10.3390/en14206578.
Abstract (sommario):
This paper proposes a second-order thermal model for electrical machines. The goal of this model is the prediction of the average winding temperature during short and long thermal transients up to the steady-state conditions. First, the thermal parameters of the electrical machine are determined by a DC test. Then, the proposed model is characterized and validated using AC tests. The accuracy of the proposed thermal model has been verified comparing the computed temperatures with the measured ones. The maximum error found during the thermal transient is lower than 3%, an excellent result comparing the complexity of a total enclosed fan cooled induction motor and the simplicity of the proposed model.
39
Zaylaa, Amira, Souad Oudjemia, Jamal Charara e Jean-Marc Girault. "n-Order and maximum fuzzy similarity entropy for discrimination of signals of different complexity: Application to fetal heart rate signals". Computers in Biology and Medicine 64 (settembre 2015): 323–33. http://dx.doi.org/10.1016/j.compbiomed.2015.03.006.
40
Vlysidis, Michail, e Yiannis Kaznessis. "Solving Stochastic Reaction Networks with Maximum Entropy Lagrange Multipliers". Entropy 20, n. 9 (12 settembre 2018): 700. http://dx.doi.org/10.3390/e20090700.
Abstract (sommario):
The time evolution of stochastic reaction networks can be modeled with the chemical master equation of the probability distribution. Alternatively, the numerical problem can be reformulated in terms of probability moment equations. Herein we present a new alternative method for numerically solving the time evolution of stochastic reaction networks. Based on the assumption that the entropy of the reaction network is maximum, Lagrange multipliers are introduced. The proposed method derives equations that model the time derivatives of these Lagrange multipliers. We present detailed steps to transform moment equations to Lagrange multiplier equations. In order to demonstrate the method, we present examples of non-linear stochastic reaction networks of varying degrees of complexity, including multistable and oscillatory systems. We find that the new approach is as accurate and significantly more efficient than Gillespie’s original exact algorithm for systems with small number of interacting species. This work is a step towards solving stochastic reaction networks accurately and efficiently.
41
Dr. Prashant Bharge, Arunoday Jaju,. "Robotic Process Automation (RPA): Process prioritization using Cognitive Complexity matrix". Psychology and Education Journal 57, n. 9 (5 gennaio 2021): 6133–40. http://dx.doi.org/10.17762/pae.v57i9.2688.
Abstract (sommario):
The process automation using robotic processes automation (RPA) has been witnessing an increasing trend of interest in recent days. However, when it comes to selection of processes for automation, among various factors process complexity is not given enough weightage. Also there are fewer researches regarding process selection and the factors impacting this decision. This research gives a methodology for selecting processes based on the complexity so that the organization can implement RPA with the optimum benefits. With this approach we can prioritize the processes in order to gain the maximum profit from the automation. This approach will also segregate the processes in which RPA automation will not result into significant amount of benefit
42
Rao Challagundla, Papa, P. Sumithabhashini e P. Chandrasekhar Reddy. "Low Complexity Signal Detector for MIMO MCCDMA System for Longer Delay Channel". International Journal of Engineering & Technology 7, n. 3.12 (20 luglio 2018): 423. http://dx.doi.org/10.14419/ijet.v7i3.12.16121.
Abstract (sommario):
In recent years Multiple-input multiple-output (MIMO) Multi carrier code division multiple access (MCCDMA), which combines the advantage of diversities with high spectral efficiency has drawn great attention. In this paper we introduce a novel low-complexity multiple-input multiple-output (MIMO) MMSE detector tailored for MCDCDMA systems, suitable for frequency selective channel. The proposed detector begins with estimation of the minimum mean square error (MMSE) on less reliable symbols followed by iterative de-correlation as post-detection processing for mitigating multiple access interferences. Efficient high-throughput VLSI architecture is used to achieve superior performance compared to the conventional MMSE detectors. The performance of the proposed MMSE detector is close to the efficient maximum likelihood, with significant complexity reduction over higher order constellations. The efficiency of MIMO MCCDMA over high order constellations and its quality retentions are verified through MATLAB BER simulation.
43
Qin, Chuan, Kehui Sun e Shaobo He. "Characteristic Analysis of Fractional-Order Memristor-Based Hypogenetic Jerk System and Its DSP Implementation". Electronics 10, n. 7 (1 aprile 2021): 841. http://dx.doi.org/10.3390/electronics10070841.
Abstract (sommario):
In this paper, a fractional-order memristive model with infinite coexisting attractors is investigated. The numerical solution of the system is derived based on the Adomian decomposition method (ADM), and its dynamic behaviors are analyzed by means of phase diagrams, bifurcation diagrams, Lyapunov exponent spectrum (LEs), dynamic map based on SE complexity and maximum Lyapunov exponent (MLE). Simulation results show that it has rich dynamic characteristics, including asymmetric coexisting attractors with different structures and offset boosting. Finally, the digital signal processor (DSP) implementation verifies the correctness of the solution algorithm and the physical feasibility of the system.
44
Nguyen, Huu Minh, Xuan Nam Tran, Van Bien Pham e Cong Dinh Nguyen. "Low-Complexity Estimation for Spatially Modulated Physical-Layer Network Coding Systems". Wireless Communications and Mobile Computing 2018 (1 ottobre 2018): 1–13. http://dx.doi.org/10.1155/2018/6310519.
Abstract (sommario):
This paper proposes a low-complexity signal estimator at the relay node for a spatially modulated physical-layer network coding system. In the considered system, the two terminal nodes use spatial modulation to transmit their signals to the relay node during the multiple access phase. Based on the channel quantization method, we propose a low-complexity estimator which can detect both antenna indices and M-QAM symbols using successive interference cancellation (SIC). Moreover, we design signal constellations for a combined signal component at the relay for arbitrary M-QAM modulation. The obtained constellations allow further reduction of the computational complexity of the estimator. Performance evaluations show that the proposed estimator can achieve near-optimal error performance while requiring significantly less computational complexity compared with the maximum-likelihood detector, particularly with high-order modulation.
45
Hamza, Mukhtar Fatihu. "Improved Decentralized Fractional-Order Control of Higher-Order Systems Using Modified Flower Pollination Optimization". Algorithms 17, n. 3 (21 febbraio 2024): 94. http://dx.doi.org/10.3390/a17030094.
Abstract (sommario):
Due to increased complexity and interactions between various subsystems, higher-order MIMO systems present difficulties in terms of stability and control performance. This study effort provides a novel, all-encompassing method for creating a decentralized fractional-order control technique for higher-order systems. Given the greater number of variables that needed to be optimized for fractional order control in higher-order, multi-input, multi-output systems, the modified flower pollination optimization algorithm (MFPOA) optimization technique was chosen due to its rapid convergence speed and minimal computational effort. The goal of the design is to improve control performance. Maximum overshoot (Mp), rising time (tr), and settling time (ts) are the performance factors taken into consideration. The MFPOA approach is used to improve the settings of the proposed decentralized fractional-order proportional-integral-derivative (FOPID) controller. By exploring the parameter space and converging on the best controller settings, the MFPOA examines the parameter space and satisfies the imposed constraints by maintaining system stability. To evaluate the suggested approach, simulation studies on two systems are carried out. The results show that by decreasing the loop interactions between subsystems with improved stability, the decentralized control with the MFPOA-based FOPID controller provides better control performance.
46
Miller, David J., e Lian Yan. "Approximate Maximum Entropy Joint Feature Inference Consistent with Arbitrary Lower-Order Probability Constraints: Application to Statistical Classification". Neural Computation 12, n. 9 (1 settembre 2000): 2175–207. http://dx.doi.org/10.1162/089976600300015105.
Abstract (sommario):
We propose a new learning method for discrete space statistical classifiers. Similar to Chow and Liu (1968) and Cheeseman (1983), we cast classification/inference within the more general framework of estimating the joint probability mass function (p.m.f.) for the (feature vector, class label) pair. Cheeseman's proposal to build the maximum entropy (ME) joint p.m.f. consistent with general lower-order probability constraints is in principle powerful, allowing general dependencies between features. However, enormous learning complexity has severely limited the use of this approach. Alternative models such as Bayesian networks (BNs) require explicit determination of conditional independencies. These may be difficult to assess given limited data. Here we propose an approximate ME method, which, like previous methods, incorporates general constraints while retaining quite tractable learning. The new method restricts joint p.m.f. support during learning to a small subset of the full feature space. Classification gains are realized over dependence trees, tree-augmented naive Bayes networks, BNs trained by the Kutato algorithm, and multilayer perceptrons. Extensions to more general inference problems are indicated. We also propose a novel exact inference method when there are several missing features.
47
Wang, Fan, Hui Han, Jian Wang e Ya Nan Liu. "The Complexity Evaluation Method of Electromagnetic Environment Based on Statistical Characteristics Analysis". Applied Mechanics and Materials 321-324 (giugno 2013): 779–84. http://dx.doi.org/10.4028/www.scientific.net/amm.321-324.779.
Abstract (sommario):
An objective complexity evaluation method of electromagnetic environment is presented based on statistical characteristics analysis. In order to quantize variation characteristics and statistical law of electromagnetic environment, evaluation factors are introduced such as relative variation, average variational ratio, maximum variational ratio, standard deviation and skewness of power spectral density. Besides, evaluation factors such as time occupancy, spectrum occupancy, space occupancy and Average energy value are utilized to conduct the objective evaluation comprehensively and accurately in time, frequency, space and energy domains. The practicability of this method is validated by monitoring data. Results show that this method can effectively evaluate the complexity of electromagnetic environment.
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Zhang, Guanghua, Zonglin Gu, Qiannan Zhao, Jingqiu Ren e Weidang Lu. "A Threshold-Based Max-log-MPA Low Complexity Multiuser Detection Algorithm". Sensors 20, n. 4 (13 febbraio 2020): 1016. http://dx.doi.org/10.3390/s20041016.
Abstract (sommario):
Sparse Code Multiple Access (SCMA) technology is a new multiple access scheme based on non-orthogonal spread spectrum technology, which was proposed by Huawei in 2014. In the algorithm application of this technology, the original Message Passing Algorithm (MPA) has slow convergence speed and high algorithm complexity. The threshold-based MPA has a high Bit Error Ratio (BER) when the threshold is low. In the Maximum logarithm Message Passing Algorithm (Max-log-MPA), the approximation method is used, which will cause some messages to be lost and the detection performance to be poor. Therefore, in order to solve the above problems, a Threshold-Based Max-log-MPA (T-Max-log-MPA) low complexity multiuser detection algorithm is proposed in this paper. The Maximum logarithm (Max-log) algorithm is combined with threshold setting, and the stability of user nodes is considered as a necessary condition for decision in the algorithm. Before message updating, the user information nodes are judged whether the necessary conditions for the stability of the user node have been met, and then the threshold is determined. Only users who meet the threshold condition and pass the necessary condition of user node stability can be decoded in advance. In the whole process, the logarithm domain MPA algorithm is used to convert an exp operation and a multiplication operation into a maximum value and addition operation. The simulation results show that the proposed algorithm can effectively reduce the computational complexity while ensuring the BER, and with the increase of signal-to-noise ratio, the effect of the Computational Complexity Reduction Ratio (CCRR) is more obvious.
49
Sulttan, Mohammed Qasim. "A New Approach of Detection Algorithm for Reducing Computation Complexity of MIMO systems". Indonesian Journal of Electrical Engineering and Computer Science 1, n. 1 (1 gennaio 2016): 159. http://dx.doi.org/10.11591/ijeecs.v1.i1.pp159-167.
Abstract (sommario):
<p>Multiple-Input Multiple-Output (MIMO) technique is a key technology to strengthen and achieve high-speed and high-throughput wireless communications. . In recent years, it was observed that frequent detecting techniques could improve the performance (e.g., symbol error rate ‘SER’) of different modern digital communication systems. But these systems faced a problem of high complexity for the practical implementation. To solve the problem of high complexity, this work proposed Frequent Improve K-best Sphere Decoding (FIKSD) algorithm with stopping rule depending on the Manhattan metric. Manhattan metric is proposed to use with FIKSD in order to achieve the lowest complexity. FIKSD is a powerful tool to achieve a high performance close to the maximum likelihood (ML), with less complexity. The simulation results show a good reduction in computation complexity with a cost of slight performance degradation within 1dB; the proposed FIKSD requires 0% to 94% and 82% to 97% less complexity than Improved K-best Sphere Decoder (IKSD) and K-best Sphere Decoder (KSD) respectively. This makes the algorithm more suitable for implementation in wireless communication systems.</p>
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Liu, Ke Wen, e Quan Liu. "Study of FCLSD Algorithm Performance Based on LTE System". Applied Mechanics and Materials 195-196 (agosto 2012): 96–103. http://dx.doi.org/10.4028/www.scientific.net/amm.195-196.96.
Abstract (sommario):
Soft-output complex list sphere decoding algorithm is a low-complexity MIMO detection algorithm and its BER performance approximates that of Maximum-Likelihood. However, it has a problem of not fixed complexity, and which make it very difficult to implement. To resolve this and try best to retain the advantages of the algorithm, a modified algorithmfixed complex list sphere decoding algorithm was proposed. Based on LTE TDD system, this paper studies the performance of the FCLSD algorithm. The simulation results show that: the BER performance of the FCLSD algorithm is close to that of the CLSD algorithm. However, when the number of antennas and modulation order increasing, the FCLSD algorithm is non-constrained of spherical radius and has fixed complexity. In addition, hardware implementation of the FCLSD algorithm could be carried out by parallel processing, thereby greatly reducing the algorithm complexity. So it is a high-performance algorithm of great potential.