Relevant bibliographies by topics / Adaptive signal processing / Journal articles

Journal articles on the topic 'Adaptive signal processing'

To see the other types of publications on this topic, follow the link: Adaptive signal processing.
Author: Grafiati
Published: 4 June 2021
Last updated: 30 July 2024

Create a spot-on reference in APA, MLA, Chicago, Harvard, and other styles

Select a source type:

Consult the top 50 journal articles for your research on the topic 'Adaptive signal processing.'

Next to every source in the list of references, there is an 'Add to bibliography' button. Press on it, and we will generate automatically the bibliographic reference to the chosen work in the citation style you need: APA, MLA, Harvard, Chicago, Vancouver, etc.

You can also download the full text of the academic publication as pdf and read online its abstract whenever available in the metadata.

Browse journal articles on a wide variety of disciplines and organise your bibliography correctly.

1

Morgan, D. "Adaptive signal processing." IEEE Transactions on Acoustics, Speech, and Signal Processing 34, no. 4 (August 1986): 1017–18. http://dx.doi.org/10.1109/tassp.1986.1164869.

Full text
APA, Harvard, Vancouver, ISO, and other styles
2

Brewster, R. L. "Adaptive Signal Processing." Electronics and Power 32, no. 7 (1986): 545. http://dx.doi.org/10.1049/ep.1986.0314.

Full text
APA, Harvard, Vancouver, ISO, and other styles
3

Sibul, Leon H., and Teresa L. Dixon. "Environmentallly adaptive signal processing." Journal of the Acoustical Society of America 101, no. 5 (May 1997): 3157. http://dx.doi.org/10.1121/1.419091.

Full text
APA, Harvard, Vancouver, ISO, and other styles
4

Wellstead, P. E. "Book Review: Adaptive Signal Processing." International Journal of Electrical Engineering & Education 23, no. 4 (October 1986): 375–76. http://dx.doi.org/10.1177/002072098602300429.

Full text
APA, Harvard, Vancouver, ISO, and other styles
5

Lindquist, C. "Book reviews - Adaptive signal processing." IEEE Control Systems Magazine 7, no. 4 (August 1987): 51. http://dx.doi.org/10.1109/mcs.1987.1105343.

Full text
APA, Harvard, Vancouver, ISO, and other styles
6

Haykin, Simon. "Guest Editorial: Adaptive Signal Processing." Optical Engineering 31, no. 6 (1992): 1143. http://dx.doi.org/10.1117/12.60706.

Full text
APA, Harvard, Vancouver, ISO, and other styles
7

Resnikoff, Howard L. "Wavelets and adaptive signal processing." Optical Engineering 31, no. 6 (1992): 1229. http://dx.doi.org/10.1117/12.57515.

Full text
APA, Harvard, Vancouver, ISO, and other styles
8

Chakrabarti, N. B. "Transform Domain Adaptive Signal Processing." IETE Journal of Research 35, no. 2 (March 1989): 52–60. http://dx.doi.org/10.1080/03772063.1989.11436792.

Full text
APA, Harvard, Vancouver, ISO, and other styles
9

Harteneck, M., and R. W. Stewart. "Adaptive signal processing JAVA applet." IEEE Transactions on Education 44, no. 2 (May 2001): 6 pp. http://dx.doi.org/10.1109/13.925850.

Full text
APA, Harvard, Vancouver, ISO, and other styles
10

Chen, Walter Y., and Richard A. Haddad. "Dual mode adaptive signal processing." Computers & Electrical Engineering 18, no. 3-4 (May 1992): 261–75. http://dx.doi.org/10.1016/0045-7906(92)90019-a.

Full text
APA, Harvard, Vancouver, ISO, and other styles
11

Ľoncová, Jana, and Ján Ochodnický. "Adaptive Algorithms in Radar Signal Processing." Science & Military 19, no. 1 (2024): 15–25. http://dx.doi.org/10.52651/sam.a.2024.1.15-25.

Full text
Abstract:
The development of modern technologies has fundamentally transformed the field of radar signal and data processing. With the use of advanced algorithms and computational power, radars are now capable of extracting crucial information from received signals, facilitating improved target identification and tracking. This article presents some of the advanced technologies employed in radar signal and data processing and their impact on adaptability of radar systems. It traces the evolution of radar technology from old systems to the present, emphasizing the benefits of adaptive radar signal processing, which includes algorithms such as adaptive beamforming, Space-Time Adaptive Processing, and the integration of Machine Learning and Artificial Intelligence. In conclusion, challenges, and future prospects in the field of radar systems are discussed, with a focus on the potential integration of Artificial Intelligence methods, Cognitive radars, and Multiple Input Multiple Output technologies. Despite technical obstacles, opportunities emerge to enhance the performance of radar systems and achieve new levels of efficiency.
APA, Harvard, Vancouver, ISO, and other styles
12

Cowan, C. F. N., R. F. Woods, J. P. Heron, P. Power, and F. J. Sweeney. "Advances in adaptive signal processing: totally adaptive systems." Annual Reviews in Control 25 (January 2001): 55–64. http://dx.doi.org/10.1016/s1367-5788(01)00006-2.

Full text
APA, Harvard, Vancouver, ISO, and other styles
13

Cowan, C. F. N., R. F. Woods, J. P. Heron, P. Power, and F. J. Sweeney. "Advances in Adaptive Signal Processing: Totally Adaptive Systems." IFAC Proceedings Volumes 31, no. 22 (August 1998): 185–94. http://dx.doi.org/10.1016/s1474-6670(17)35941-4.

Full text
APA, Harvard, Vancouver, ISO, and other styles
14

Garmatyuk, Dmitriy, and Matthew Brenneman. "Adaptive Multicarrier OFDM SAR Signal Processing." IEEE Transactions on Geoscience and Remote Sensing 49, no. 10 (October 2011): 3780–90. http://dx.doi.org/10.1109/tgrs.2011.2165546.

Full text
APA, Harvard, Vancouver, ISO, and other styles
15

Moustakides, G. V. "Locally optimum adaptive signal processing algorithms." IEEE Transactions on Signal Processing 46, no. 12 (1998): 3315–25. http://dx.doi.org/10.1109/78.735306.

Full text
APA, Harvard, Vancouver, ISO, and other styles
16

Sztipanovits, Janos, Gabor Karsai, and Ted Bapty. "Self-adaptive software for signal processing." Communications of the ACM 41, no. 5 (May 1998): 66–73. http://dx.doi.org/10.1145/274946.274958.

Full text
APA, Harvard, Vancouver, ISO, and other styles
17

Stewart, R. W., M. Harteneck, and S. Weiss. "Interactive teaching of adaptive signal processing." Engineering Science & Education Journal 9, no. 4 (August 1, 2000): 161–68. http://dx.doi.org/10.1049/esej:20000404.

Full text
APA, Harvard, Vancouver, ISO, and other styles
18

Nejevenko, E. S., and A. A. Sotnikov. "Adaptive modeling for hydroacoustic signal processing." Pattern Recognition and Image Analysis 16, no. 1 (January 2006): 5–8. http://dx.doi.org/10.1134/s1054661806010020.

Full text
APA, Harvard, Vancouver, ISO, and other styles
19

Murano, K. "Adaptive Signal Processing Applied in Telecommunications." IFAC Proceedings Volumes 25, no. 14 (July 1992): 431–41. http://dx.doi.org/10.1016/s1474-6670(17)50772-7.

Full text
APA, Harvard, Vancouver, ISO, and other styles
20

McWhirter, J. G. "Algorithmic engineering in adaptive signal processing." IEE Proceedings F Radar and Signal Processing 139, no. 3 (1992): 226. http://dx.doi.org/10.1049/ip-f-2.1992.0028.

Full text
APA, Harvard, Vancouver, ISO, and other styles
21

Etter, Delores M. "An introduction to adaptive signal processing." Computers & Electrical Engineering 18, no. 3-4 (May 1992): 189–93. http://dx.doi.org/10.1016/0045-7906(92)90013-4.

Full text
APA, Harvard, Vancouver, ISO, and other styles
22

Bugallo, Mónica F., Luca Martino, and Jukka Corander. "Adaptive importance sampling in signal processing." Digital Signal Processing 47 (December 2015): 36–49. http://dx.doi.org/10.1016/j.dsp.2015.05.014.

Full text
APA, Harvard, Vancouver, ISO, and other styles
23

Bitmead, Robert R., C. Richard Johnson, and Clifford R. Pollock. "Optical adaptive signal processing: An appraisal." International Journal of Adaptive Control and Signal Processing 5, no. 2 (March 1991): 87–92. http://dx.doi.org/10.1002/acs.4480050202.

Full text
APA, Harvard, Vancouver, ISO, and other styles
24

Niang, Oumar, Abdoulaye Thioune, Éric Deléchelle, and Jacques Lemoine. "Spectral Intrinsic Decomposition Method for Adaptive Signal Representation." ISRN Signal Processing 2012 (December 13, 2012): 1–10. http://dx.doi.org/10.5402/2012/457152.

Full text
Abstract:
We propose a new method called spectral intrinsic decomposition (SID) for the representation of nonlinear signals. This approach is based on the spectral decomposition of partial differential equation- (PDE-) based operators which interpolate the characteristic points of a signal. The SID’s components which are the eigenvectors of these PDE interpolation operators underlie the new signal decomposition-reconstruction method. The usefulness and the efficiency of this method is illustrated, in signal reconstruction or denoising aim, in some examples using artificial and pathological signals.
APA, Harvard, Vancouver, ISO, and other styles
25

Raheem, Syed, and Dr Subhashish Bose. "Subband Adaptive Filter in Signal Processing Application." Revista Gestão Inovação e Tecnologias 11, no. 4 (August 4, 2021): 4096–109. http://dx.doi.org/10.47059/revistageintec.v11i4.2434.

Full text
Abstract:
Owing to the powerful digital signal processors and the improvement of advanced edge adaptive algorithms there are an extraordinary number of various applications in which adaptive filters are utilized. Subband adaptive filtering algorithms can build the assembly pace of framework ID undertakings when the info signal is hued. The adaptive filter can filter the dubious noise signal, track the difference in the signal, and consistently change the boundaries to accomplish the ideal filtering impact. Another standardized subband adaptive filtering algorithm has been proposed, whose primary benefit is the lower computational intricacy when contrasted with best in class subband approaches, while keeping up comparable union execution. A connection between the adaptive subband coefficients and the ideal full band move work is determined, and the algorithm is demonstrated to create an asymptotically unprejudiced arrangement. The proficiency of the adaptive filters basically relies upon the plan procedure utilized and the algorithm of variation. The adaptive filters can be analogical plans, digital or blended which show their benefits and inconveniences, for instance, the analogical filters are low power consuming and fast response, however they address balance issues, which influence the activity of the variation algorithm.
APA, Harvard, Vancouver, ISO, and other styles
26

Minasian, Robert A. "Ultra-Wideband and Adaptive Photonic Signal Processing of Microwave Signals." IEEE Journal of Quantum Electronics 52, no. 1 (January 2016): 1–13. http://dx.doi.org/10.1109/jqe.2015.2499729.

Full text
APA, Harvard, Vancouver, ISO, and other styles
27

Zou, Dong Lan. "Research on the Sensor Coarse Signal Processing Model Based on Adaptive Genetic Algorithm." Applied Mechanics and Materials 443 (October 2013): 342–45. http://dx.doi.org/10.4028/www.scientific.net/amm.443.342.

Full text
Abstract:
With the rapid development of electronic information science and network transmission technology, the signal processing technology has been widely applied to various fields, which is the most important component of signal detection and transmission, and the key signal processing technology for processing sensor crude signals. Based on this, the experimental system of sensor coarse signal processing model is established, and in the experimental system, the transformer can carry out signal recognition for voltage and current, the use of PC microcontroller and embedded AD converter carries out analog / digital conversion for sensor crude signal. For the amplification process of sensor coarse signal, the use of adaptive genetic algorithm carries out mathematical modeling, the realization of the signal identification, acquisition and processing functions through software programming control. Finally, the intelligent processing of sensor coarse signal is successfully completed by the experiment system, and the signal processing effect is given as well.
APA, Harvard, Vancouver, ISO, and other styles
28

LIBEROVSKIY, NIKITA Y., VLADIMIR S. PRIPUTIN, and DENIS S. CHIROV. "A REVIEW OF RESEARCH ON ADAPTIVE BEAMFORMING AND DIGITAL SIGNAL PROCESSING." H&ES Research 13, no. 6 (2021): 16–21. http://dx.doi.org/10.36724/2409-5419-2021-13-6-16-21.

Full text
Abstract:
Introduction: Recently, there has been an active development of algorithms for adaptive beamforming. Such work is required in order to improve the efficiency of receiving a useful signal, especially in mobile communication systems. This article provides an overview of research on this topic. Papers devoted to the improvement of the classical least mean square algorithm, blind signal separation methods, antenna selection algorithms in MIMO systems and other topics of adaptive signal processing are presented. Practical relevance: Adaptive beamforming is a key development for modern wireless communication systems, in particular 5G. Increasing requirements that impose a limitation on the spectral bandwidth of the signal and its center frequency with limited signal power lead to the strategy of forming a narrow signal transmission beam, thereby increasing the energy efficiency of signal transmission and reducing the overhead associated with the reception of various interference. This article provides an overview of studies on this topic. The results of the analysis of works devoted to the improvement of the classical algorithm for minimizing the mean square error, blind signal separation, antenna selection algorithms in systems of several antennas, and other topics of adaptive signal processing are presented. Discussion: It is shown that the main directions of research are focused on the improvement of classical diagramming algorithms, as well as on the improvement of methods for receiving digital signals in MIMO systems. Algorithms for recognizing the type of signal modulation, an algorithm for blind separation of second-order signals, an improved algorithm for automatic gain control, an algorithm for suppressing noise-like interference, and an algorithm for estimating radiation pattern parameters were also considered.
APA, Harvard, Vancouver, ISO, and other styles
29

Ma, Bo Le, Jing Fang Cheng, and Wei Zhang. "Research of Vector Hydrophone Adaptive Signal Processing." Applied Mechanics and Materials 423-426 (September 2013): 2496–506. http://dx.doi.org/10.4028/www.scientific.net/amm.423-426.2496.

Full text
Abstract:
As a useful tool for line spectrum detection in underwater signal ,ALE has been used wildly. But there are still some problems to influence the effect of ALE. This paper gives three problems on ALE and analyses these.Then by the characteristics of vector hydrophone and a improved variable step size LMS,this paper constructs a cascade double input with variable step size based on vector hydrophone line spectrum enhancer . This algorithm restrains the noise of main channel twice ,meanwhile controls the noise in reference channel , so as to improve signal to noise ratio better. At the same time ,because of adopting the improved variable step size LMS, the steady-state error is reduced. From the results of simulation and experiment, the method presented in this paper can have a better effect of line spectrum enhancement.
APA, Harvard, Vancouver, ISO, and other styles
30

Claasen, T., and W. Mecklenbrauker. "Adaptive techniques for signal processing in communications." IEEE Communications Magazine 23, no. 11 (November 1985): 8–19. http://dx.doi.org/10.1109/mcom.1985.1092451.

Full text
APA, Harvard, Vancouver, ISO, and other styles
31

Bisgaard, Nikolai, and Rob Anton Jurjen De Vries. "HEARING INSTRUMENT WITH ADAPTIVE DIRECTIONAL SIGNAL PROCESSING." Journal of the Acoustical Society of America 133, no. 2 (2013): 1198. http://dx.doi.org/10.1121/1.4790241.

Full text
APA, Harvard, Vancouver, ISO, and other styles
32

Amari, S., and A. Cichocki. "Adaptive blind signal processing-neural network approaches." Proceedings of the IEEE 86, no. 10 (1998): 2026–48. http://dx.doi.org/10.1109/5.720251.

Full text
APA, Harvard, Vancouver, ISO, and other styles
33

Plataniotis, K. N., D. Androutsos, and A. N. Venetsanopoulos. "Adaptive fuzzy systems for multichannel signal processing." Proceedings of the IEEE 87, no. 9 (1999): 1601–22. http://dx.doi.org/10.1109/5.784243.

Full text
APA, Harvard, Vancouver, ISO, and other styles
34

Perić, Zoran, Vlado Delić, Zoran Stamenković, and David Pokrajac. "Advanced Signal Processing and Adaptive Learning Methods." Computational Intelligence and Neuroscience 2019 (November 3, 2019): 1–2. http://dx.doi.org/10.1155/2019/5428615.

Full text
APA, Harvard, Vancouver, ISO, and other styles
35

Rzeszewski, T. S., and P. H. Wyant. "Picture crispening by adaptive digital signal processing." IEEE Transactions on Consumer Electronics CE-33, no. 2 (1987): 71–76. http://dx.doi.org/10.1109/tce.1987.6446492.

Full text
APA, Harvard, Vancouver, ISO, and other styles
36

Stewart, R. W., J. J. Soraghan, and T. S. Durrani. "Noncanonical FIR filters and adaptive signal processing." Electronics Letters 25, no. 6 (1989): 414. http://dx.doi.org/10.1049/el:19890285.

Full text
APA, Harvard, Vancouver, ISO, and other styles
37

Ise, Shiro, and Hideki Tachibana. "Active sound absorber using adaptive signal processing." Journal of the Acoustical Society of Japan (E) 17, no. 6 (1996): 305–10. http://dx.doi.org/10.1250/ast.17.305.

Full text
APA, Harvard, Vancouver, ISO, and other styles
38

Kadlec, Jir̆í. "Adaptive system identification and signal processing algorithms." Automatica 31, no. 10 (October 1995): 1519–21. http://dx.doi.org/10.1016/0005-1098(95)90000-4.

Full text
APA, Harvard, Vancouver, ISO, and other styles
39

Chen, Junlin, and Lei Wang. "Energy-Adaptive Signal Processing Under Renewable Energy." Journal of Signal Processing Systems 84, no. 3 (November 2, 2015): 399–412. http://dx.doi.org/10.1007/s11265-015-1071-8.

Full text
APA, Harvard, Vancouver, ISO, and other styles
40

Besson, Olivier, and Stephanie Bidon. "Adaptive Processing With Signal Contaminated Training Samples." IEEE Transactions on Signal Processing 61, no. 17 (September 2013): 4318–29. http://dx.doi.org/10.1109/tsp.2013.2269048.

Full text
APA, Harvard, Vancouver, ISO, and other styles
41

Johnson, Paul A. "Overview of signal processing for adaptive optics." Digital Signal Processing 1, no. 1 (January 1991): 24–26. http://dx.doi.org/10.1016/1051-2004(91)90090-8.

Full text
APA, Harvard, Vancouver, ISO, and other styles
42

Naik, Sanjeev. "Advanced misfire detection using adaptive signal processing." International Journal of Adaptive Control and Signal Processing 18, no. 2 (March 2004): 181–98. http://dx.doi.org/10.1002/acs.789.

Full text
APA, Harvard, Vancouver, ISO, and other styles
43

Singh, Hema, and Rakesh Mohan Jha. "Trends in Adaptive Array Processing." International Journal of Antennas and Propagation 2012 (2012): 1–20. http://dx.doi.org/10.1155/2012/361768.

Full text
Abstract:
Enormous progress has been made during the past five decades in the area of adaptive array processing. Increased computational power has resulted in many practical applications of optimum algorithms. The present paper deals with many facets of array signal processing and adaptive beam forming. It provides a comprehensive description of various beam-forming schemes, adaptive algorithms to adjust the required weighting on antenna elements, direction-of-arrival estimation methods, including their performance comparison. The effects of various types of errors on the performance of an array system are illustrated along with their remedial measures. Since array signal processing has widespread applications, the study is carried out across various disciplines.
APA, Harvard, Vancouver, ISO, and other styles
44

Yang, Dan, Bin Xu, Lin Lin Ye, and Xu Wang. "Speech Enhancement Using Wavelet Neural Network with Sub-Band Adaptive Matched Filter." Advanced Engineering Forum 2-3 (December 2011): 127–30. http://dx.doi.org/10.4028/www.scientific.net/aef.2-3.127.

Full text
Abstract:
Wavelet Neural Network (WNN) Is a Time-frequency Analysis Method, which Detects the Subtle Small Changes in the Signal Frequency Domain. Adaptive Filter Provides a Kind of Simple and Applied Method for Processing Signals in Noise. in this Paper, we Proposed a New Speech Enhancement Technique which Is Based on Wavelet Neural Network Using Adaptive Matched Filter Adjusting Weight. we Choose the Signal with Noise Pollution as the Input Signal and then Put it to the Trained Wavelet Neural Network. Wavelet Decomposition and Wavelet Neural Network Weights Processing Adopt Signal Sub-band Adaptive Matched Filter, the Output Signal of Wavelet Neural Network Is an Approximation Form of Original Signal. the Results Show that the WNN Is a Quite Effective Method for the Speech Enhancement and Improving the Ration of Signal to Noise.
APA, Harvard, Vancouver, ISO, and other styles
45

Mao, Minghui, Jun Chang, Jiachen Sun, Shan Lin, and Zihan Wang. "Research on VMD-Based Adaptive TDLAS Signal Denoising Method." Photonics 10, no. 6 (June 11, 2023): 674. http://dx.doi.org/10.3390/photonics10060674.

Full text
Abstract:
We propose an adaptive algorithm that is a Variational Mode Decomposition (VMD) optimized by the particle swarm optimization (PSO) algorithm, named PSO-VMD. The method selects the envelope entropy of the last intrinsic mode function (IMF) in the VMD as the fitness function of the PSO and 1/10 of the maximum value of the correlation coefficient between the IMFs and the standard signal as the threshold of the correlation coefficient. In the processing of simulated and experimental second harmonic signals, a series of standards, including the same correlation coefficient threshold and standard signal, are used to adaptively achieve noise reduction processing. After processing a simulated signal using PSO-VMD, the signal-to-noise ratio (SNR) was improved by 4.03877 dB and the correlation coefficient (R2) between the gas concentration and the second harmonic maximum was improved from 0.97743 to 0.99782. In the processing of an experimental signal, the correlation coefficient (R2) was 0.99733. The mean value and standard deviation of the second harmonic signal of multiple cycles processed by PSO-VMD were improved compared to the unprocessed experimental signal. This demonstrated that the method has the advantage of being reliable and stable.
APA, Harvard, Vancouver, ISO, and other styles
46

Dai, Jing, Rui Zhou, and Shi Tang. "Design Method of DLMS Adaptive Filter Based on FPGA." Applied Mechanics and Materials 182-183 (June 2012): 685–89. http://dx.doi.org/10.4028/www.scientific.net/amm.182-183.685.

Full text
Abstract:
This paper proposed DLMS algorithm which is suitable for real-time signal processing. The algorithm adopts hardware multiplier and pipeline technology to accelerate the operation of the system. By analyzing the time sequence and spectrum of the output signals, the attenuation of the interference signals is about 51dB. It can further demonstrate the high quality and high speed of the DLMS algorithm to filter out the interference signals, and well handle the relationship between the resources and speed of FPGA to meet the requirements of high-speed signal processing.
APA, Harvard, Vancouver, ISO, and other styles
47

Martinek, Radek, Martina Ladrova, Michaela Sidikova, Rene Jaros, Khosrow Behbehani, Radana Kahankova, and Aleksandra Kawala-Sterniuk. "Advanced Bioelectrical Signal Processing Methods: Past, Present and Future Approach—Part I: Cardiac Signals." Sensors 21, no. 15 (July 30, 2021): 5186. http://dx.doi.org/10.3390/s21155186.

Full text
Abstract:
Advanced signal processing methods are one of the fastest developing scientific and technical areas of biomedical engineering with increasing usage in current clinical practice. This paper presents an extensive literature review of the methods for the digital signal processing of cardiac bioelectrical signals that are commonly applied in today’s clinical practice. This work covers the definition of bioelectrical signals. It also covers to the extreme extent of classical and advanced approaches to the alleviation of noise contamination such as digital adaptive and non-adaptive filtering, signal decomposition methods based on blind source separation and wavelet transform.
APA, Harvard, Vancouver, ISO, and other styles
48

Carpenter, Daniel P. "Adaptive Signal Processing, Hierarchy, and Budgetary Control in Federal Regulation." American Political Science Review 90, no. 2 (June 1996): 283–302. http://dx.doi.org/10.2307/2082885.

Full text
Abstract:
Control over agency budgets is a critical tool of political influence in regulatory decision making, yet the causal mechanism of budgetary control is unclear. Do budgetary manipulations influence agencies by imposing resource constraints or by transmitting powerful signals to the agency? I advance and test a stochastic process model of adaptive signal processing by a hierarchical agency to address this question. The principal findings of the paper are two. First, presidents and congressional committees achieve budgetary control over agencies not by manipulating aggregate resource constraints but by transmitting powerful signals through budget shifts. Second, bureaucratic hierarchy increases the agency's response time in processing budgetary signals, limiting the efficacy of the budget as a device of political control. I also show that the magnitude of agency response to budgetary signals increased for executive-branch agencies after 1970 due to executive oversight reforms. I conclude by discussing the limits of budgetary manipulations as a device of political control and the response of elected authorities to adaptive signal processing by agencies.
APA, Harvard, Vancouver, ISO, and other styles
49

Tyapkin, V. N., V. N. Ratushnyak, D. D. Dmitriev, and A. B. Gladyshev. "Increase of noise suppression efficiency due to correction of frequency characteristics of receiving channels in the navigation equipment of consumers." Spacecrafts & Technologies 2, no. 1 (2018): 30–37. http://dx.doi.org/10.26732/2618-7957-2018-1-30-37.

Full text
Abstract:
Space-time signal processing in adaptive electronic systems, including navigation, remains the subject of intensive research, as it allows to improve the efficiency of receiving useful signals under the influence of natural or intentional interference. The bibliography on this subject is very extensive and includes a large number of articles of scientific and applied nature, dissertations, monographs, patent materials. Much of this work has references to monographs by R. Monzingo and B. Widrow, which set out the basic principles, criteria and algorithms of spatial-temporal signal processing. To date, the development of space-time signal processing is largely constrained by the imperfection of the element base. The use of modern navigation equipment consumers high-speed signal processors that implement advanced methods and algorithms of digital signal processing, provides the ability of digital methods to form the desired beam pattern of the antenna system and to adjust the frequency characteristics of the reception channels, to implement complex algorithms for optimal processing of useful signals, operative to control the main operation modes of equipment. One of the most important applications of space-time signal processing is noise suppression, and its effectiveness depends on the degree of inter-channel correlation of these signals received by antenna elements of the adaptive antenna array. To maximize the coefficient of interference suppression required the adoption of measures on alignment of frequency and phase characteristics of the receiving circuits, and high precision computation of weighting coefficients. The article considers the questions of spatial filtering of the interference when adaptive interference compensator adjusted frequency characteristics of the receiving channels, and means of satellite navigation. Gradient algorithm of spatial compensation of noise, and also influence of adaptive correction of frequency characteristics of receiving channels on quality of suppression of noise is presented. The formation of a directional diagram of a multi-element adaptive antenna array with spatial noise suppression is demonstrated by modeling in the Matlab environment.
APA, Harvard, Vancouver, ISO, and other styles
50

Ou, Jianping, Jun Zhang, and Ronghui Zhan. "Processing Technology Based on Radar Signal Design and Classification." International Journal of Aerospace Engineering 2020 (January 17, 2020): 1–19. http://dx.doi.org/10.1155/2020/4673763.

Full text
Abstract:
It is well known that the application of radar is becoming more and more popular with the development of the signal technology progress. This paper lists the current radar signal research, the technical progress achieved, and the existing limitations. According to radar signal respective characteristics, the design and classification of the radar signal are introduced to reflect signal’s differences and advantages. The multidisciplinary processing technology of the radar signal is classified and compared in details referring to adaptive radar signal process, pulse signal management, digital filtering signal mode, and Doppler method. The transmission process of radar signal is summarized, including the transmission steps of radar signal, the factors affecting radar signal transmission, and radar information screening. The design method of radar signal and the corresponding signal characteristics are compared in terms of performance improvement. Radar signal classification method and related influencing factors are also contrasted and narrated. Radar signal processing technology is described in detail including multidisciplinary technology synthesis. Adaptive radar signal process, pulse compression management, and digital filtering Doppler method are very effective technical means, which has its own unique advantages. At last, the future research trends and challenges of technologies of the radar signals are proposed. The conclusions obtained are beneficial to promote the further promotion applications both in theory and practice. The study work of this paper will be useful for choosing more reasonable radar signal processing technology methods.
APA, Harvard, Vancouver, ISO, and other styles
You might also be interested in the bibliographies on the topic 'Adaptive signal processing' for other source types:
Dissertations / Theses Books
We offer discounts on all premium plans for authors whose works are included in thematic literature selections. Contact us to get a unique promo code!

To the bibliography