Bibliographies thématiques / Sensor decoding

Littérature scientifique sur le sujet « Sensor decoding »

Auteur : Grafiati
Publié le 10 mars 2023

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Articles de revues sur le sujet "Sensor decoding"

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Flamary, R., N. Jrad, R. Phlypo, M. Congedo et A. Rakotomamonjy. « Mixed-Norm Regularization for Brain Decoding ». Computational and Mathematical Methods in Medicine 2014 (2014) : 1–13. http://dx.doi.org/10.1155/2014/317056.

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This work investigates the use of mixed-norm regularization for sensor selection in event-related potential (ERP) based brain-computer interfaces (BCI). The classification problem is cast as a discriminative optimization framework where sensor selection is induced through the use of mixed-norms. This framework is extended to the multitask learning situation where several similar classification tasks related to different subjects are learned simultaneously. In this case, multitask learning helps in leveraging data scarcity issue yielding to more robust classifiers. For this purpose, we have introduced a regularizer that induces both sensor selection and classifier similarities. The different regularization approaches are compared on three ERP datasets showing the interest of mixed-norm regularization in terms of sensor selection. The multitask approaches are evaluated when a small number of learning examples are available yielding to significant performance improvements especially for subjects performing poorly.
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Snippe, Herman P. « Parameter Extraction from Population Codes : A Critical Assessment ». Neural Computation 8, no 3 (avril 1996) : 511–29. http://dx.doi.org/10.1162/neco.1996.8.3.511.

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In perceptual systems, a stimulus parameter can be extracted by determining the center-of-gravity of the response profile of a population of neural sensors. Likewise at the motor end of a neural system, center-of-gravity decoding, also known as vector decoding, generates a movement direction from the neural activation profile. We evaluate these schemes from a statistical perspective, by comparing their statistical variance with the minimum variance possible for an unbiased parameter extraction from the noisy neuronal ensemble activation profile. Center-of-gravity decoding can be statistically optimal. This is the case for regular arrays of sensors with gaussian tuning profiles that have an output described by Poisson statistics, and for arrays of sensors with a sinusoidal tuning profile for the (angular) parameter estimated. However, there are also many cases in which center-of-gravity decoding is highly inefficient. This includes the important case where sensor positions are very irregular. Finally, we study the robustness of center-of-gravity decoding against response nonlinearities at different stages of an information processing hierarchy. We conclude that, in neural systems, instead of representing a parameter explicitly, it is safer to leave the parameter coded implicitly in a neuronal ensemble activation profile.
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Dash, Debadatta, Alan Wisler, Paul Ferrari, Elizabeth Moody Davenport, Joseph Maldjian et Jun Wang. « MEG Sensor Selection for Neural Speech Decoding ». IEEE Access 8 (2020) : 182320–37. http://dx.doi.org/10.1109/access.2020.3028831.

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Okunsky, M. V., et N. V. Nesterova. « Velodyne LIDAR method for sensor data decoding ». IOP Conference Series : Materials Science and Engineering 516 (26 avril 2019) : 012018. http://dx.doi.org/10.1088/1757-899x/516/1/012018.

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Aineto, Diego, Sergio Jimenez et Eva Onaindia. « Observation Decoding with Sensor Models : Recognition Tasks via Classical Planning ». Proceedings of the International Conference on Automated Planning and Scheduling 30 (1 juin 2020) : 11–19. http://dx.doi.org/10.1609/icaps.v30i1.6640.

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Observation decoding aims at discovering the underlying state trajectory of an acting agent from a sequence of observations. This task is at the core of various recognition activities that exploit planning as resolution method but there is a general lack of formal approaches that reason about the partial information received by the observer or leverage the distribution of the observations emitted by the sensors. In this paper, we formalize the observation decoding task exploiting a probabilistic sensor model to build more accurate hypothesis about the behaviour of the acting agent. Our proposal extends the expressiveness of former recognition approaches by accepting observation sequences where one observation of the sequence can represent the reading of more than one variable, thus enabling observations over actions and partially observable states simultaneously. We formulate the probability distribution of the observations perceived when the agent performs an action or visits a state as a classical cost planning task that is solved with an optimal planner. The experiments will show that exploiting a sensor model increases the accuracy of predicting the agent behaviour in four different contexts.
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Parfenov, V. I., et V. D. Le. « DISTRIBUTED DETECTION BASED ON USING SOFT DECISION DECODING IN A FUSION CENTER ». Telecommunications, no 1 (2022) : 2–9. http://dx.doi.org/10.31044/1684-2588-2022-0-1-2-9.

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In this work, distributed detection by data from many sensors in the wireless sensor system is considered. A decision-making algorithm based on using soft-decision decoding in a fusion center is synthesized. Its gain in efficiency compared to efficiency of the algorithm based on hard-decision scheme is shown. It is noted that this algorithm is a generalization of earlier developed algorithms.
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Ganin, Dmitriy V., Mokhammed A. Y. Damdam et Aleksandr L. Savkin. « PERMUTATION DECODING IN LOW-POWER WIRELESS SENSOR NETWORKS ». Автоматизация процессов управления 2, no 68 (2022) : 37–44. http://dx.doi.org/10.35752/1991-2927-2022-2-68-37-44.

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Wireless sensor networks are currently considered for many subject areas as effective communication systems, including, for example, industrial and agricultural facilities and enterprises, monitoring of sensors of transport security systems, medicine applications, environmental and weather monitoring, etc. In such systems, the correction code (CC) is a classic approach used to increase the reliability of the data transmission channel while simultaneously reducing the required transmitted signal power, called the energy gain code. At the same time, the power of the transmitter is reduced due to additional power consumption in the receiver decoder. Stronger codes provide better performance with lower power requirements, but have more complex decoders with higher power consumption than relatively simple error control systems. If the additional power consumption at the output of the decoder exceeds the savings in transmitted power due to the use of CC, then such a code will not be energy efficient compared to a system with a non-redundant code. Various codes can be used to protect data, while the best codes for which the critical distance turns out to be large according to a number of studies are codes with a low parity check density. The paper proposes an alternative variant based on the synthesis of a permutation decoding system using the method of localization of a limited number of permutations and the organization of additional parity checks exclusively for the verification bits of the CC using the Bayesian approach to iterative transformations of integer soft solutions of symbols.
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Yufei, Wu, Wang Dandan et Zhu Yanwei. « Research on the Advantages of Digital Sensor Equipment in Language Audio-Visual and Oral Teaching ». Journal of Sensors 2021 (30 novembre 2021) : 1–13. http://dx.doi.org/10.1155/2021/3006397.

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Digital sensors use biotechnology and information processing technology to strengthen the processing of relevant visual and auditory information, which is helpful to ensure that the receiver can obtain more accurate information, so as to improve the learning effect and reduce the impact on the environment. This paper designs an experiment to explore the role of digital sensors in language audio-visual teaching, which provides a reference for the application of digital sensors in the future. The impulse response function in sensor technology is introduced. The speech time domain envelope and time-varying mouth area of the sensor device are calculated. The auditory attention transfer detection based on line of sight rotation estimation is carried out through the auditory attention decoding fusion technology and the sensor auditory attention conversion detection method. At the same time, the characteristic of sensor heog signal is analyzed. The results show that the algorithm proposed in this paper has good results.
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Cordeiro, Paulo J., et Pedro Assunção. « Distributed Coding/Decoding Complexity in Video Sensor Networks ». Sensors 12, no 3 (29 février 2012) : 2693–709. http://dx.doi.org/10.3390/s120302693.

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Dwivedi, Anany, Helen Groll et Philipp Beckerle. « A Systematic Review of Sensor Fusion Methods Using Peripheral Bio-Signals for Human Intention Decoding ». Sensors 22, no 17 (23 août 2022) : 6319. http://dx.doi.org/10.3390/s22176319.

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Humans learn about the environment by interacting with it. With an increasing use of computer and virtual applications as well as robotic and prosthetic devices, there is a need for intuitive interfaces that allow the user to have an embodied interaction with the devices they are controlling. Muscle–machine interfaces can provide an intuitive solution by decoding human intentions utilizing myoelectric activations. There are several different methods that can be utilized to develop MuMIs, such as electromyography, ultrasonography, mechanomyography, and near-infrared spectroscopy. In this paper, we analyze the advantages and disadvantages of different myography methods by reviewing myography fusion methods. In a systematic review following the PRISMA guidelines, we identify and analyze studies that employ the fusion of different sensors and myography techniques, while also considering interface wearability. We also explore the properties of different fusion techniques in decoding user intentions. The fusion of electromyography, ultrasonography, mechanomyography, and near-infrared spectroscopy as well as other sensing such as inertial measurement units and optical sensing methods has been of continuous interest over the last decade with the main focus decoding the user intention for the upper limb. From the systematic review, it can be concluded that the fusion of two or more myography methods leads to a better performance for the decoding of a user’s intention. Furthermore, promising sensor fusion techniques for different applications were also identified based on the existing literature.
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Thèses sur le sujet "Sensor decoding"

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Illangakoon, Chathura. « On joint source-channel decoding and interference cancellation in CDMA-based large-scale wireless sensor networks ». IEEE, 2013. http://hdl.handle.net/1993/22019.

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Motivated by potential applications in wireless sensor networks, this thesis considers the problem of communicating a large number of correlated analog sources over a Gaussian multiple-access channel using non-orthogonal code-division multiple-access (CDMA). A joint source-channel decoder is presented which can exploit the inter-source correlation for interference reduction in the CDMA channel. This decoder uses a linear minimum mean square error (MMSE) multi-user detector (MUD) in tandem with a MMSE joint source decoder (JSD) for multiple sources to achieve a computational complexity that scales with the number of sources. The MUD and the JSD, then iteratively exchange extrinsic information to improve the interference cancellation. Experimental results show that, compared to a non-iterative decoder, the proposed iterative decoder is more robust against potential performance degradation due to correlated channel interference and offers better near far resistance.
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KOBAYASHI, Kentaro, Takaya YAMAZATO, Hiraku OKADA et Masaaki KATAYAMA. « Joint Channel Decoding of Spatially and Temporally Correlated Data in Wireless Sensor Networks ». IEEE, 2008. http://hdl.handle.net/2237/12086.

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Pishro-Nik, Hossein. « Applications of Random Graphs to Design and Analysis of LDPC Codes and Sensor Networks ». Diss., Georgia Institute of Technology, 2005. http://hdl.handle.net/1853/7722.

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This thesis investigates a graph and information theoretic approach to design and analysis of low-density parity-check (LDPC) codes and wireless networks. In this work, both LDPC codes and wireless networks are considered as random graphs. This work proposes solutions to important theoretic and practical open problems in LDPC coding, and for the first time introduces a framework for analysis of finite wireless networks. LDPC codes are considered to be one of the best classes of error-correcting codes. In this thesis, several problems in this area are studied. First, an improved decoding algorithm for LDPC codes is introduced. Compared to the standard iterative decoding, the proposed decoding algorithm can result in several orders of magnitude lower bit error rates, while having almost the same complexity. Second, this work presents a variety of bounds on the achievable performance of different LDPC coding scenarios. Third, it studies rate-compatible LDPC codes and provides fundamental properties of these codes. It also shows guidelines for optimal design of rate-compatible codes. Finally, it studies non-uniform and unequal error protection using LDPC codes and explores their applications to data storage systems and communication networks. It presents a new error-control scheme for volume holographic memory (VHM) systems and shows that the new method can increase the storage capacity by more than fifty percent compared to previous schemes. This work also investigates the application of random graphs to the design and analysis of wireless ad hoc and sensor networks. It introduces a framework for analysis of finite wireless networks. Such framework was lacking from the literature. Using the framework, different network properties such as capacity, connectivity, coverage, and routing and security algorithms are studied. Finally, connectivity properties of large-scale sensor networks are investigated. It is shown how unreliability of sensors, link failures, and non-uniform distribution of nodes affect the connectivity of sensor networks.
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Kobayashi, Kentaro, Takaya Yamazato, Hiraku Okada et Masaaki Katayama. « Iterative Joint Channel-Decoding Scheme Using the Correlation of Transmitted Information Sequences in Sensor Networks ». IEEE, 2006. http://hdl.handle.net/2237/7755.

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Bekjarova, Milka. « Packet erasure correcting codes for wireless sensor networks : implementation and field trial measurements ». Master's thesis, Alma Mater Studiorum - Università di Bologna, 2012. http://amslaurea.unibo.it/3558/.

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This thesis regards the Wireless Sensor Network (WSN), as one of the most important technologies for the twenty-first century and the implementation of different packet correcting erasure codes to cope with the ”bursty” nature of the transmission channel and the possibility of packet losses during the transmission. The limited battery capacity of each sensor node makes the minimization of the power consumption one of the primary concerns in WSN. Considering also the fact that in each sensor node the communication is considerably more expensive than computation, this motivates the core idea to invest computation within the network whenever possible to safe on communication costs. The goal of the research was to evaluate a parameter, for example the Packet Erasure Ratio (PER), that permit to verify the functionality and the behavior of the created network, validate the theoretical expectations and evaluate the convenience of introducing the recovery packet techniques using different types of packet erasure codes in different types of networks. Thus, considering all the constrains of energy consumption in WSN, the topic of this thesis is to try to minimize it by introducing encoding/decoding algorithms in the transmission chain in order to prevent the retransmission of the erased packets through the Packet Erasure Channel and save the energy used for each retransmitted packet. In this way it is possible extend the lifetime of entire network.
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Kaardal, Joel Thomas. « Decoding the Computations of Sensory Neurons ». Thesis, University of California, San Diego, 2018. http://pqdtopen.proquest.com/#viewpdf?dispub=10633582.

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The nervous system encodes information about external stimuli through sophisticated computations performed by vast networks of sensory neurons. Since the space of all possible stimuli is much larger than the space of those that are ultimately meaningful, dimensionality reduction techniques were developed to identify the subspace of stimulus space relevant to neural activity. However, dimensionality reduction methods provide limited insight into the nonlinear functions that build the nervous system’s internal model of the world. In Chapter 2, the functional basis is introduced that transforms the relevant subspace to a basis that describes the computational function of the subunits that make up the neural circuitry. This functional basis is used to uncover novel insights about the computations performed by neurons in low-level vision and, later on, high-level auditory circuitry. For the latter, significant barriers are found in the capability of current dimensionality reduction methods to recover the relevant subspaces of high-level sensory neurons. This barrier is caused by the relative difficulty of stimulating high-level sensory neurons, which are often unresponsive to noise stimuli, while still maintaining a thorough exploration of the stimulus distribution. In response, a new approach to dimensionality reduction is formulated in Chapter 3 called the low-rank maximum noise entropy method that makes it possible to overcome challenges presented by high-level sensory systems. In Chapter 4, functional bases derived from the relevant subspaces recovered by the low-rank maximum noise entropy method are employed to study the neural computations performed by high-level auditory neurons.

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Das, Tanmoy. « Exploiting Hidden Resources to Design Collision-Embracing Protocols for Emerging Wireless Networks ». The Ohio State University, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=osu1565807656641553.

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Solda', Silvia. « Design of low-power analog circuits for analog decoding and wireless sensors nodes ». Doctoral thesis, Università degli studi di Padova, 2009. http://hdl.handle.net/11577/3426488.

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The first part of this work concerns analog decoding. It presents the design of the I/O interface for a fully analog iterative decoder for a serially concatenated convolutional code and of a fully analog Trellis Coded Modulation (TCM) decoder for error correction in multi-level (ML) flash memories. The iterative decoder represents a significant step ahead in the evolution of analog decoders due to its reconfigurability in both block length and code rate. Moreover, with an efficiency of 2.1nJ/bit, it outperforms digital decoders with the same block length of a factor up to 50. The potential performance and limitations of the analog approach for a TCM decoder have been investigated considering a 4-state and an 8-state decoder, both developed in a 0.18um standard CMOS process. In the second part of the thesis, the design of a low-power transceiver chipset for ultra wideband impulse radio (UWB-IR) is presented, with particular emphasis on the transmitter design. In particular, the transmitter uses a novel combined mixer and power amplifier to generate a Gaussian pulse with 1.25GHz bandwith and center frequency of 7.875GHz. The combined MRX-PA includes a monolithic transformer to reach a maximum output voltage swing of 3.2Vpp, necessary to ensure the required link distance of 10 meters. The transformer has been designed in order to maximize the power efficiency and at the same time to realize a fourth-order ladder filter, so as to reduce the transmitter out-of band emissions. The efficiency of this design has been compared with state-of-the-art UWB-IR transmitters, showing how the proposed solution leads to an improvement in the transmitter efficiency of a factor of almost 10.
La prima parte di questo lavoro di tesi e' dedicata alla decodifica analogica e presenta la progettazione di un'interfaccia di I/O per un decodificatore iterattivo completamente analogico per un codice convoluzionale concatenato in serie e di un decoder analogico per Trellis Coded Modulation (TCM) per la correzione degli errori in memorie Flash multi-livello. Il decodificatore iterattivo rappresenta un grosso passo avanti nell'evoluzione dei decodificatori analogici in quanto e' possibile riconfigurarne sia la lunghezza di blocco che il rate del codice. Per di piu', con un'efficienza di 2.1nJ/bit, migliora fino a 50 volte le prestazioni in termini di efficienza dei decodificatori digitali con la stessa lunghezza di blocco. Le potenziali prestazioni e le limitazioni dell'approccio analogico per un decodificatore per TCM sono state investigate considerando due diversi decodificatori, uno a 4 stati ed uno ad 8 stati, entrambi sviluppati in un processo CMOS standard con una lunghezza di canale di 0.18um. Nella seconda parte della tesi viene presentato il design di un transciver per una radio ad impulsi a banda larga (UWB-IR), con particolare enfasi sulla progettazione del trasmettitore. Il trasmettitore utilizza una nuova combinazione di mixer e amplificatore di potenza per generare un impulso gaussiano con una larghezza di banda di 1.25GHz ed una frequenza centrale di 7.875GHz. Il nuovo circuito, inoltre, include un trasformatore monolitico in modo tale da generare una tensione di uscita di 3.2Vpp, necessaria per garantire la distanza di connessione richiesta di almeno 10 metri. Il trasformatore e' stato progettato in modo da massimizzare l'efficienza in termini di potenza e, allo stesso tempo, realizzare un filtro ladder del quarto ordine al fine di ridurre le emissioni fuori banda del trasmettitore stesso. Confrontando l'efficienza di questo design con trasmettori per UWB-IR allo stato dell'arte si e' visto come la soluzione da noi proposta porti ad un miglioramento dell'efficienza del trasmettitore di un fattore pari a 10.
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Romero, Arandia Iñigo. « Reading out neural populations : shared variability, global fluctuations and information processing ». Doctoral thesis, Universitat Pompeu Fabra, 2017. http://hdl.handle.net/10803/404684.

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Entendre l'origen i la funció de l'activitat de poblacions neuronals, i com aquesta activitat es relaciona amb els estímuls sensorials, les decisions o les accions motores és un gran repte per les neurociències. En aquest treball hem analitzat l'activitat de desenes de neurones enregistrades a l'escorça visual primària de micos mentre se'ls presentaven escletxes sinusoïdals en diferents orientacions. Hem trobat que les fluctuacions globals de la xarxa mesurades mitjançant l'activitat de la població modulen la selectivitat de les neurones de forma multiplicativa i additiva. A més, l'activitat de la població també afecta la informació present en grups petits de neurones, depenent de la modulació que ha provocat a la selectivitat d'aquestes. La informació de la població sencera, però, no canvia amb aquestes fluctuacions. A la segona part hem desenvolupat un mètode per mesurar 'correlacions diferencials' amb dades limitades. En aplicar-ho a les dades experimentals hem aconseguit la primera estimació preliminar de la grandària d'aquestes correlacions que limiten la informació. Els nostres resultats contribueixen a l'avenç en la comprensió de la codi ficació d'informació en poblacions neuronals, i alhora generen noves preguntes sobre com aquestes processen i transmeten informació.
Entender el origen y la función de la actividad de poblaciones neuronales, y cómo esta actividad se relaciona con los estímulos sensoriales, las decisiones o las acciones motoras es un gran desafio en neurociencia. En este trabajo hemos analizado la actividad de decenas de neuronas registradas en la corteza visual primaria de monos mientras rejillas sinusoidales en diferentes orientaciones eran presentadas. Hemos encontrado que las fluctuaciones globales de la red medidas mediante la actividad de la población modulan la selectividad de las neuronas de manera multiplicativa y aditiva. Además, la actividad de la población también afecta a la información presente en grupos pequeños de neuronas, dependiendo de la modulación que ha provocado en la selectividad de estas neuronas. La información en la población completa, sin embargo, no varía con estas fluctuaciones. En la segunda parte hemos desarrollado un método para medir 'correlaciones diferenciales' con datos limitados. Al aplicarlo a los datos experimentales hemos obtenido la primera estimación preliminar del tamaño de estas correlaciones que limitan la información. Nuestros resultados contribuyen al avance del entendimiento sobre la codi ficación de la información en poblaciones neuronales, y al mismo tiempo generan más preguntas sobre cómo éstas procesan y transmiten información.
Understanding the sources and the role of the spiking activity of neural populations, and how this activity is related to sensory stimuli, decisions or motor actions is a crucial challenge in neuroscience. In this work, we analyzed the spiking activity of tens of neurons recorded in the primary visual cortex of macaque monkeys while drifting sinusoidal gratings were presented in di erent orientations. We found that global uctuations of the network measured by the population activity a ect the tuning of individual neurons both multiplicatively and additively. Population activity also has an impact in the information of small ensembles, which depends on the kind of modulation that the tuning of those neurons undergoes. Interestingly, the total information of the network is not altered by these uctuations. In the second part, we developed a method to measure 'di erential correlations' from limited amount of data, and obtained the rst, although preliminary, estimate in experimental data. Our results have important implications for information coding, and they open new questions about the way information is processed and transmitted by the spiking activity of neural populations.
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Wåhlin, Peter. « Enhanching the Human-Team Awareness of a Robot ». Thesis, Mälardalens högskola, Akademin för innovation, design och teknik, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:mdh:diva-16371.

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The use of autonomous robots in our society is increasing every day and a robot is no longer seen as a tool but as a team member. The robots are now working side by side with us and provide assistance during dangerous operations where humans otherwise are at risk. This development has in turn increased the need of robots with more human-awareness. Therefore, this master thesis aims at contributing to the enhancement of human-aware robotics. Specifically, we are investigating the possibilities of equipping autonomous robots with the capability of assessing and detecting activities in human teams. This capability could, for instance, be used in the robot's reasoning and planning components to create better plans that ultimately would result in improved human-robot teamwork performance. we propose to improve existing teamwork activity recognizers by adding intangible features, such as stress, motivation and focus, originating from human behavior models. Hidden markov models have earlier been proven very efficient for activity recognition and have therefore been utilized in this work as a method for classification of behaviors. In order for a robot to provide effective assistance to a human team it must not only consider spatio-temporal parameters for team members but also the psychological.To assess psychological parameters this master thesis suggests to use the body signals of team members. Body signals such as heart rate and skin conductance. Combined with the body signals we investigate the possibility of using System Dynamics models to interpret the current psychological states of the human team members, thus enhancing the human-awareness of a robot.
Användningen av autonoma robotar i vårt samhälle ökar varje dag och en robot ses inte längre som ett verktyg utan som en gruppmedlem. Robotarna arbetar nu sida vid sida med oss och ger oss stöd under farliga arbeten där människor annars är utsatta för risker. Denna utveckling har i sin tur ökat behovet av robotar med mer människo-medvetenhet. Därför är målet med detta examensarbete att bidra till en stärkt människo-medvetenhet hos robotar. Specifikt undersöker vi möjligheterna att utrusta autonoma robotar med förmågan att bedöma och upptäcka olika beteenden hos mänskliga lag. Denna förmåga skulle till exempel kunna användas i robotens resonemang och planering för att ta beslut och i sin tur förbättra samarbetet mellan människa och robot. Vi föreslår att förbättra befintliga aktivitetsidentifierare genom att tillföra förmågan att tolka immateriella beteenden hos människan, såsom stress, motivation och fokus. Att kunna urskilja lagaktiviteter inom ett mänskligt lag är grundläggande för en robot som ska vara till stöd för laget. Dolda markovmodeller har tidigare visat sig vara mycket effektiva för just aktivitetsidentifiering och har därför använts i detta arbete. För att en robot ska kunna ha möjlighet att ge ett effektivt stöd till ett mänskligtlag måste den inte bara ta hänsyn till rumsliga parametrar hos lagmedlemmarna utan även de psykologiska. För att tyda psykologiska parametrar hos människor förespråkar denna masteravhandling utnyttjandet av mänskliga kroppssignaler. Signaler så som hjärtfrekvens och hudkonduktans. Kombinerat med kroppenssignalerar påvisar vi möjligheten att använda systemdynamiksmodeller för att tolka immateriella beteenden, vilket i sin tur kan stärka människo-medvetenheten hos en robot.

The thesis work was conducted in Stockholm, Kista at the department of Informatics and Aero System at Swedish Defence Research Agency.

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Livres sur le sujet "Sensor decoding"

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Derval, Diana. Right Sensory Mix : Decoding Customers' Behavior and Preferences. Springer Berlin / Heidelberg, 2021.

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Janczuk, Elena. Stałe motywy metafizyczne w twórczości Mariny Cwietajewej. University of Warsaw Press, 2021. http://dx.doi.org/10.31338/uw.9788323546054.

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The analysis of metaphysical motifs in Marina Tsvetaeva’s lyric poetry, their occurrence and tendency to continuous metamorphosis. Tsvetaeva made a profound change in understanding the essence of the 20th century poetry and her reflections on the world and man’s place in it brought her closer to philosophy. The motifs she used had been present in philosophical discourse as they referred to such notions as space and time, body and soul, life and death, light and darkness, silence and sound, god. To a scholar and a reader Tsvetaeva’s poetry means constant discovering and decoding senses and emotions hidden in sophisticated words.
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Troisi, Alfonso. Nonverbal Communication. Oxford University Press, 2017. http://dx.doi.org/10.1093/med/9780199393404.003.0007.

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Humans use two different means to exchange information: language and nonverbal communication. Often nonverbal signals emphasize and specify what is being said with words. Yet sometimes they collide, and the words are contradicted by what seeps through facial expression, gesture, and posture. This chapter discusses two theoretical frameworks for studying these nonverbal behaviors. The first approach (the emotional model) aims at unveiling the emotional state from facial expression and gesture. The second approach (the behavioral ecology model) analyzes the social meaning of nonverbal behavior, regardless of the emotional state of the sender of nonverbal signals. The two models are not incompatible and can be integrated to study nonverbal behavior. Yet, the behavioral ecology model explains some findings that are not accounted for by the emotional model. The final part of the chapter deals with neuropsychiatric conditions, such as Williams syndrome and prosopagnosia, that alter the encoding and decoding of nonverbal signals. The impact of these conditions on real-life social behavior can be dramatic, which shows the adaptive relevance of nonverbal communication.
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Chapitres de livres sur le sujet "Sensor decoding"

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von Rickenbach, Pascal, et Roger Wattenhofer. « Decoding Code on a Sensor Node ». Dans Distributed Computing in Sensor Systems, 400–414. Berlin, Heidelberg : Springer Berlin Heidelberg, 2008. http://dx.doi.org/10.1007/978-3-540-69170-9_27.

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Ituero, Pablo, Gorka Landaburu, Javier Del Ser, Marisa López-Vallejo, Pedro M. Crespo, Vicente Atxa et Jon Altuna. « Joint Source-Channel Decoding ASIP Architecture for Sensor Networks ». Dans Embedded Software and Systems, 98–108. Berlin, Heidelberg : Springer Berlin Heidelberg, 2007. http://dx.doi.org/10.1007/978-3-540-72685-2_10.

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Takahashi, Yohsuke, et Takeshi Ito. « Structure and Function of CDPK : A Sensor Responder of Calcium ». Dans Coding and Decoding of Calcium Signals in Plants, 129–46. Berlin, Heidelberg : Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-20829-4_9.

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Huang, Yu-Hsiung, Wei-Chun Chen et Su-Chu Hsu. « Creative Design of Gaussian Sensor System with Encoding and Decoding ». Dans Lecture Notes in Computer Science, 385–95. Cham : Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-78361-7_29.

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Aragon, Nicolas, Jean Pierre Cances, Imad El Qachchach, Philippe Gaborit et Oussama Habachi. « Extended Low Rank Parity Check Codes and Their Efficient Decoding for Multisource Wireless Sensor Networks ». Dans Ubiquitous Networking, 41–55. Cham : Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-58008-7_4.

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Kist, Andreas M., Laura D. Knogler, Daniil A. Markov, Tugce Yildizoglu et Ruben Portugues. « Whole-Brain Imaging Using Genetically Encoded Activity Sensors in Vertebrates ». Dans Decoding Neural Circuit Structure and Function, 321–41. Cham : Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-57363-2_13.

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Clemens, Jan, et Mala Murthy. « The Use of Computational Modeling to Link Sensory Processing with Behavior in Drosophila ». Dans Decoding Neural Circuit Structure and Function, 241–60. Cham : Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-57363-2_9.

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Khomokhoana, Pakiso J., et Liezel Nel. « Decoding Source Code Comprehension : Bottlenecks Experienced by Senior Computer Science Students ». Dans Communications in Computer and Information Science, 17–32. Cham : Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-35629-3_2.

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Gold, Joshua I. « Multiple Roles of Experience in Decoding the Neural Representation of Sensory Stimuli ». Dans Percept, Decision, Action : Bridging the Gaps, 92–107. Chichester, UK : John Wiley & Sons, Ltd, 2008. http://dx.doi.org/10.1002/9780470034989.ch8.

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Del Ser, Javier, Mikel Mendicute, Pedro M. Crespo, Sergio Gil-Lopez et Ignacio Olabarrieta. « Joint Source-Channel-Network Decoding and Blind Estimation of Correlated Sensors Using Concatenated Zigzag Codes ». Dans Ad-Hoc, Mobile and Wireless Networks, 30–41. Berlin, Heidelberg : Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-04383-3_3.

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Actes de conférences sur le sujet "Sensor decoding"

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Salah, Hamed, Hazem A. Ahmed, Joerg Robert et Albert Heuberger. « Maximum Likelihood decoding for non-synchronized UHF RFID tags ». Dans 2016 IEEE Topical Conference on Wireless Sensors and Sensor Networks (WiSNet). IEEE, 2016. http://dx.doi.org/10.1109/wisnet.2016.7444330.

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Liu, Jun, Weitao Xu et Wen Hu. « Energy Efficient LPWAN Decoding via Joint Sparse Approximation ». Dans SenSys '18 : The 16th ACM Conference on Embedded Networked Sensor Systems. New York, NY, USA : ACM, 2018. http://dx.doi.org/10.1145/3274783.3275165.

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Morey, W. W., G. A. Ball, G. Meltz, J. R. Dunphy et A. D. Kersey. « Advances in Fiber Grating Sensors ». Dans Photosensitivity and Quadratic Nonlinearity in Glass Waveguides. Washington, D.C. : Optica Publishing Group, 1995. http://dx.doi.org/10.1364/pqn.1995.pmc.1.

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Properly annealed fiber gratings can be used as sensor transducer elements at temperatures of 400° C over long periods of time without measurable changes. At 650° C, however, a problem was observed with creep or hysteresis of the grating response. At even higher temperatures diffusion of the core material will become a problem for long term operation. A couple new decoding schemes for fiber grating sensors use matched gratings and acousto-optic tunable filter in the decoding unit These systems can measure many grating transducer elements simultaneously with high sensitivity. Short cavity fiber lasers that utilized fiber gratings can also act as sensor transducer elements giving one ultra high sensitivities that are limited by the fundamental noise in the fiber. One fiber laser sensor uses hetrodyning to generate a signal that can be measured on an RF spectrum analyzer. New techniques for simultaneous measurement of temperature and strain will also be discussed.
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Li, Yanpeng, Ziyun Miao, Xiangpeng Xiao, Zhen Li, Zhijun Yan et Qizhen Sun. « Implantable optical fiber sensor for monitoring the stress evolution in lithium-sulfur battery ». Dans CLEO : Applications and Technology. Washington, D.C. : Optica Publishing Group, 2022. http://dx.doi.org/10.1364/cleo_at.2022.atu5m.4.

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We report the implantable optical fiber sensor for monitoring the cathode stress evolution in the lithium-sulfur battery. The operando decoding of the chemo-mechanics events of Li-sulfur battery is successfully realized.
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Shuiyin Liu, Xiaomei Fu et Cong Ling. « Lattice decoding for cooperative communications using the segment LLL algorithm ». Dans Sensor Signal Processing for Defence (SSPD 2010). IET, 2010. http://dx.doi.org/10.1049/ic.2010.0249.

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Graham, Daniel, Arnold Yim, Gang Zhou et Weizhen Mao. « Real-Time Encoding/Decoding for Pairwise Communication Over an Unreliable Sensor Network ». Dans 8th International Conference on Sensor Networks. SCITEPRESS - Science and Technology Publications, 2019. http://dx.doi.org/10.5220/0007247000690076.

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Fazal-E-Asim, Andre L. F. de Almeida, Martin Haardt, Charles C. Cavalcante et Josef A. Nossek. « Multi-Linear Encoding and Decoding for MIMO Systems ». Dans 2020 IEEE 11th Sensor Array and Multichannel Signal Processing Workshop (SAM). IEEE, 2020. http://dx.doi.org/10.1109/sam48682.2020.9104276.

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Costa, Rui A., Daniele Munaretto, Joerg Widmer et Joao Barros. « Informed network coding for minimum decoding delay ». Dans 2008 5th IEEE International Conference on Mobile Ad Hoc and Sensor Systems (MASS). IEEE, 2008. http://dx.doi.org/10.1109/mahss.2008.4660042.

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Barros, J., M. Tuchler et Seong Per Lee. « Scalable source/channel decoding for large-scale sensor networks ». Dans 2004 IEEE International Conference on Communications (IEEE Cat. No.04CH37577). IEEE, 2004. http://dx.doi.org/10.1109/icc.2004.1312628.

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Nguyen, Harrison, Luke Osborn, Mark Iskarous, Christopher Shallal, Christopher Hunt, Joseph Betthauser et Nitish Thakor. « Dynamic Texture Decoding Using a Neuromorphic Multilayer Tactile Sensor ». Dans 2018 IEEE Biomedical Circuits and Systems Conference (BioCAS). IEEE, 2018. http://dx.doi.org/10.1109/biocas.2018.8584826.

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Rapports d'organisations sur le sujet "Sensor decoding"

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Kreller, Cortney. Exploiting Cross-sensitivity by Bayesian Decoding of Mixed Potential Sensor Arrays. Office of Scientific and Technical Information (OSTI), octobre 2017. http://dx.doi.org/10.2172/1396156.

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