Les codes source-canal conjoints sont des codes réalisant simultanément une compression de données et une protection du train binaire généré par rapport à d’éventuelles erreurs de transmission. Ces codes sont non-linéaires, comme la plupart des codes de source. Leur intérêt potentiel est d’offrir de bonnes performances en termes de compression et de correction d’erreur pour des longueurs de codes réduites.La performance d’un code de source se mesure par la différence entre l’entropie de la source à compresser et le nombre moyen de bits nécessaire pour coder un symbole de cette source. La performance d’un code de canal se mesure par la distance minimale entre mots de codes ou entre suite de mots de codes, et plus généralement à l’aide du spectre des distances. Les codes classiques disposent d’outils pour évaluer efficacement ces critères de performance. Par ailleurs, la synthèse de bons codes de source ou de bons codes de canal est un domaine largement exploré depuis les travaux de Shannon. Par contre des outils analogues pour des codes source-canal conjoints, tant pour l’évaluation de performance que pour la synthèse de bons codes restaient à développer, même si certaines propositions ont déjà été faites dans le passé.Cette thèse s’intéresse à la famille des codes source-canal conjoints pouvant être décrits par des automates possédant un nombre fini d’états. Les codes quasi-arithmétiques correcteurs d’erreurs et les codes à longueurs variables correcteurs d’erreurs font partie de cette famille. La manière dont un automate peut être obtenu pour un code donné est rappelée.A partir d’un automate, il est possible de construire un graphe produit permettant de décrire toutes les paires de chemins divergeant d'un même état et convergeant vers un autre état. Nous avons montré que grâce à l’algorithme de Dijkstra, il est alors possible d’évaluer la distance libre d’un code conjoint avec une complexité polynomiale.Pour les codes à longueurs variables correcteurs d’erreurs, nous avons proposé des bornes supplémentaires, faciles à évaluer. Ces bornes constituent des extensions des bornes de Plotkin et de Heller aux codes à longueurs variables. Des bornes peuvent également être déduites du graphe produit associé à un code dont seule une partie des mots de codes a été spécifiée.Ces outils pour borner ou évaluer exactement la distance libre d’un code conjoint permettent de réaliser la synthèse de codes ayant des bonnes propriétés de distance pour une redondance donnée ou minimisant la redondance pour une distance libre donnée.Notre approche consiste à organiser la recherche de bons codes source-canal conjoints à l’aide d’arbres. La racine de l’arbre correspond à un code dont aucun bit n’est spécifié, les feuilles à des codes dont tous les bits sont spécifiés, et les nœuds intermédiaires à des codes partiellement spécifiés. Lors d’un déplacement de la racine vers les feuilles de l’arbre, les bornes supérieures sur la distance libre décroissent, tandis que les bornes inférieures croissent. Ceci permet d’appliquer un algorithme de type branch-and-prune pour trouver le code avec la plus grande distance libre, sans avoir à explorer tout l’arbre contenant les codes. L'approche proposée a permis la construction de codes conjoints pour les lettres de l'alphabet. Comparé à un schéma tandem équivalent (code de source suivi d'un code convolutif), les codes obtenus ont des performances comparables (taux de codage, distance libre) tout en étant moins complexes en termes de nombre d’état du décodeur.Plusieurs extensions de ces travaux sont en cours : 1) synthèse de codes à longueurs variables correcteurs d’erreurs formalisé comme un problème de programmation linéaire mixte sur les entiers ; 2) exploration à l’aide d’un algorithme de type A* de l’espace des codes de à longueurs variables correcteur d’erreurs. / Joint source-channel codes are codes simultaneously providing data compression and protection of the generated bitstream from transmission errors. These codes are non-linear, as most source codes. Their potential is to offer good performance in terms of compression and error-correction for reduced code lengths.The performance of a source code is measured by the difference between the entropy of the source to be compressed and the average number of bits needed to encode a symbol of this source. The performance of a channel code is measured by the minimum distance between codewords or sequences of codewords, and more generally with the distance spectrum. The classic codes have tools to effectively evaluate these performance criteria. Furthermore, the design of good source codes or good channel codes is a largely explored since the work of Shannon. But, similar tools for joint source-channel codes, for performances evaluation or for design good codes remained to develop, although some proposals have been made in the past.This thesis focuses on the family of joint source-channel codes that can be described by automata with a finite number of states. Error-correcting quasi-arithmetic codes and error-correcting variable-length codes are part of this family. The way to construct an automaton for a given code is recalled.From an automaton, it is possible to construct a product graph for describing all pairs of paths diverging from some state and converging to the same or another state. We have shown that, using Dijkstra's algorithm, it is possible to evaluate the free distance of a joint code with polynomial complexity. For errors-correcting variable-length codes, we proposed additional bounds that are easy to evaluate. These bounds are extensions of Plotkin and Heller bounds to variable-length codes. Bounds can also be deduced from the product graph associated to a code, in which only a part of code words is specified.These tools to accurately assess or bound the free distance of a joint code allow the design of codes with good distance properties for a given redundancy or minimizing redundancy for a given free distance. Our approach is to organize the search for good joint source-channel codes with trees. The root of the tree corresponds to a code in which no bit is specified, the leaves of codes in which all bits are specified, and the intermediate nodes to partially specified codes. When moving from the root to the leaves of the tree, the upper bound on the free distance decreases, while the lower bound grows. This allows application of an algorithm such as branch-and-prune for finding the code with the largest free distance, without having to explore the whole tree containing the codes.The proposed approach has allowed the construction of joint codes for the letters of the alphabet. Compared to an equivalent tandem scheme (source code followed by a convolutional code), the codes obtained have comparable performance (rate coding, free distance) while being less complex in terms of the number of states of the decoder. Several extensions of this work are in progress: 1) synthesis of error-correcting variable-length codes formalized as a mixed linear programming problem on integers, 2) Explore the search space of error-correcting variable-length codes using an algorithm such as A* algorithm.

The major contribution of this dissertation is the development of a new integrated measurement and control system for intermixed biogas and photovoltaic systems to achieve safe and optimal energy usage. Literature and field studies show that existing control methods fall short of comprehensive system optimization and fault diagnosis, hence the need to re-look these control methods. The control strategy developed in this dissertation is a considerable enhancement on existing strategies as it incorporates intelligent fuzzy logic algorithms based on C source codes developed on the MPLABX programming environment. Measurements centered on the PIC18F4550 microcontroller were carried out on existing biogas and photovoltaic installations. The designed system was able to accurately predict digester stability, quantify biogas output and carry out biogas fault detection and control. Optimized battery charging and photovoltaic fault detection and control was also successfully implemented. The system optimizes the operation and performance of biogas and photovoltaic energy generation. / Electrical Engineering / M. Tech. (Electrical Engineering)

Network coding was introduced as a means to increase throughput in communication networks when compared to routing. Network coding can be used not only to communicate messages from some nodes in the network to other nodes but are also useful when some nodes in a network are interested in computing some functions of information generated at some other nodes. Such a situation arises in sensor networks. In this work, we study three problems in network coding. First, we consider the functional source coding with side information problem wherein there is one source that generates a set of messages and one receiver which knows some functions of source messages and demands some other functions of source messages. Cognizant of the receiver's side information, the source aims to satisfy the demands of the receiver by making minimum number of coded transmissions over a noiseless channel. We use row-Latin rectangles to obtain optimal codes for a given functional source coding with side information problem. Next, we consider the multiple receiver extension of this problem, called the functional index coding problem, in which there are multiple receivers, each knowing and demanding disjoint sets of functions of source messages. The source broadcasts coded messages, called a functional index code, over a noiseless channel. For a given functional index coding problem, the restrictions the demands of the receivers pose on the code are represented using the generalized exclusive laws and it is shown that a code can be obtained using the confusion graph constructed using these laws. We present bounds on the size of an optimal code based on the parameters of the confusion graph. For the case of noisy broadcast channel, we provide a necessary and sufficient condition that a code must satisfy for correct decoding of desired functions at each receiver and obtain a lower bound on the length of an error-correcting functional index code. In the second problem, we explore relation between network function computation problems and functional index coding and Metroid representation problems. In a network computation problem, the demands of the sink nodes in a directed acyclic multichip network include functions of the source messages. We show that any network computation problem can be converted into a functional index coding problem and vice versa. We prove that a network code that satisfies all the sink demands in a network computation problem exists if and only if its corresponding functional index coding problem admits a functional index code of a specific length. Next, we establish a relation between network computation problems and representable mastoids. We show that a network computation problem in which the sinks demand linear functions of source messages admits a scalar linear solution if and only if it is matricidal with respect to a representable Metroid whose representation fulfils certain constraints dictated by the network computation problem. Finally, we study the usage of the sum-product (SP) algorithm for decoding network codes. Though lot of methods to obtain network codes exist, the decoding procedure and complexity have not received much attention. We propose a SP algorithm based decoder for network codes which can be used to decode both linear and nonlinear network codes. We pose the decoding problem at a sink node as a marginalize a product function (MPF) problem over the Boolean smearing and use the SP algorithm on a suitably constructed factor graph to perform decoding. We propose and demonstrate the usage of trace back to reduce the number of operations required to perform SP decoding. The computational complexity of performing SP decoding with and without trace back is obtained. For nonlinear network codes, we define fast decidability of a network code at sinks that demand all the source messages and identify a sufficient condition for the same. Next, for network function computation problems, we present an MPF formulation for function computation at a sink node and use the SP algorithm to obtain the value of the demanded function.