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.
Texte intégralKOBAYASHI, 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.
Texte intégralPishro-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.
Texte intégralKobayashi, 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.
Texte intégralBekjarova, 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/.
Texte intégralKaardal, Joel Thomas. « Decoding the Computations of Sensory Neurons ». Thesis, University of California, San Diego, 2018. http://pqdtopen.proquest.com/#viewpdf?dispub=10633582.
Texte intégralThe 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.
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.
Texte intégralSolda', 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.
Texte intégralLa 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.
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.
Texte intégralEntender 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.
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.
Texte intégralAnvändningen 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.
Sung, Jing-Tian, et 宋經天. « Adaptive Distributed Classification Using Soft-Decision Decoding in Wireless Sensor Networks ». Thesis, 2007. http://ndltd.ncl.edu.tw/handle/40692053768695642639.
Texte intégral國立臺灣科技大學
電機工程系
96
Distributed Classification Fusion using Error-Correcting Codes (DCFECC) has recently been proposed for wireless sensor networks. It adopts the Minimum Hamming Distance (MHD) fusion rule and performs much better than traditional classification approaches when the network has faulty sensors. Different fusion rules were proposed later. One of them is Distributed Classification fusion using Soft-decision Decoding (DCSD). The DCSD fusion rule has a considerably misclassification probability than the MHD fusion rule. However, the probability of misclassification using DCSD approach is high when the detection result is not reliable. Moreover, the transmission channel is highly noisy. Since the sensor makes its local decision without evaluating the reliability of the detection result, it may waste its power to transmit an unreliable local decision. In this work, the performance of the DCSD fusion rule is analyzed. Asymptotic performance approximation of the DCSD fusion rule is derived based on the Central Limit Theorem. Furthermore, an asymptotic upper bound on the misclassification probability is obtained. The numerical simulations are conducted to verify our analysis results. Besides, this work proposes an adaptive redetection scheme to resolve this problem of the unreliable detection results. An unreliable range is set for each sensor. If the detection result of the sensor is not located in the unreliable range, the sensor makes a local decision. Otherwise, the sensor has to make another detection. This work further proposes an adaptive retransmission scheme to reduce the misclassification probability in highly noisy channels. When a final decision made by a fusion center is unreliable, the sensor which has sent the local decision with the lowest channel reliability will be asked to retransmit its local decision by the fusion center. Performance analysis and simulation results show that the misclassification probability can be efficiently reduced through the adaptive redetection and retransmission.
« Applications of Random Graphs to Design and Analysis of LDPC Codes and Sensor Networks ». Diss., Georgia Institute of Technology, 2005. http://hdl.handle.net/1853/7464.
Texte intégralCocozza, Claudia, Saverio Francini, Gherardo Chirici, Daniele Penna, Matteo Verdone et Andrea Dani. « TreeTalker : a new device to monitor tree functional traits, from calibration to forest monitoring ». Doctoral thesis, 2023. https://hdl.handle.net/2158/1298899.
Texte intégralPerez-Orive, Javier. « Neural Oscillations and the Decoding of Sensory Information ». Thesis, 2004. https://thesis.library.caltech.edu/1992/1/JPODissertation.pdf.
Texte intégralAn important problem in neuroscience is to understand how the brain encodes information. A hypothesis is that differences in the timing of action potentials, reflecting synchronization changes among neuronal ensembles --often occurring in the context of oscillations-- can be meaningful to downstream neurons detecting coincident input. Several properties, such as active conductances, feedforward inhibition and oscillatory input, could potentially influence whether a neuron acts as a coincidence detector. Although different neural circuits in various animal groups will use different strategies to solve somewhat varying problems, there will also be many powerful solutions to coding problems that will be used repeatedly across diverse processing stages and animal phyla. The insect olfactory system, sharing many design similarities with other systems while having a reduced complexity, provides an excellent model in which to study the functional interactions of all these coding features.
This dissertation focuses on the decoding of olfactory information by the mushroom body (MB), the second relay of the insect olfactory system, which receives oscillating input from the antennal lobe (the first relay, analogous to the vertebrate olfactory bulb). Kenyon cells (KCs), the intrinsic neurons of the MB, are found to respond very specifically to odors. These responses typically consist of one or two reliable action potentials, phase-locked to the global oscillations, over extremely low baseline firing rates. This leads to a dramatic sparsening of the olfactory representation in the MB. Several circuit and intrinsic properties are found to take part in this transformation. Feedforward inhibition contributes to odor specificity and sparseness: blocking inhibitory input to the KCs broadened their odor tuning and abolished their phase-locking, supporting the idea that feedforward inhibition limits the temporal window over which KCs integrate their inputs. Voltage-dependent conductances contribute to a supralinear summation of coincident postsynaptic potentials and a reduction of their half-widths, indicating that KC intrinsic properties further contribute to coincidence detection. Taken together, these results indicate that oscillations serve as a framework on which KCs act as coincidence detectors and sparsen the olfactory representation. Abolishing the input oscillations disrupts KC odor responses, decreasing their specificity and the sparseness in the MB.
The work in this dissertation describes a mechanism for decoding timing information and indicates that not all spikes are equally relevant to downstream neurons, their specific relevance depending on whether they are correlated, within a specific phase of an oscillation cycle, with other input spikes. These general features can also provide useful insights into neural coding in more complex neural systems, where all the mechanisms described here have been separately observed. This work illustrates how these mechanisms can interact to code sensory information and bring about drastic transformations of neural representations, increasing our understanding of how nervous systems can process information.
Kasi, Patrick K. « Bayesian decoding of tactile afferents responsible for sensorimotor control ». Thesis, 2017. http://hdl.handle.net/1959.7/uws:43931.
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