Este trabalho traz a aplicação da transformada wavelet (TW) para analisar os transitórios de alta freqüência em um sistema de transmissão causados por uma falta sustentada, com o objetivo de se determinar a precisa localização da mesma. A TW, ferramenta matemática empregada neste trabalho, é uma transformação linear muito parecida com a transformada de Fourier, com uma importante diferença: ela permite a localização no tempo de diferentes componentes de freqüência de um dado sinal. Esta localização permite a detecção no tempo da ocorrência de distúrbios abruptos, tais como os transitórios ocasionados por situações de faltas. Os sinais de ondas viajantes geradas pela ocorrência da falta aparecem como distúrbios superpostos aos sinais de freqüência fundamental que são registrados pelos relés. Processando-se estes sinais pelo emprego da TW, esta pode revelar o tempo de propagação dos sinais analisados entre o ponto de ocorrência do distúrbio e a localização física do relé. Conseqüentemente, dispondo-se do intervalo de tempo entre as ondas sobre uma dada linha de transmissão, a distância do ponto de falta pode então ser facilmente determinada, sendo esta a filosofia adotada neste trabalho. O problema delineado é abordado através da implementação prática de um algoritmo computacional. Nesta implementação, o usuário pode escolher a técnica de localização a ser empregada, utilizando-se de dados registrados em um ou em ambos os terminais da linha, conforme a sua necessidade e/ou disponibilidade dos recursos necessários. Com o objetivo de testar e validar a aplicabilidade do algoritmo de localização de faltas, utilizou-se de dados de sinais faltosos obtidos através de simulações do software ATP (Altenative Transients Program), levando-se em conta vários tipos de falta em diferentes localizações ao longo da linha, com diferentes ângulos de incidência, resistências de falta, freqüência de amostragem do sinal, etc. Também foi verificada a influência do acoplamento mútuo em caso de circuitos duplos de transmissão. Os resultados alcançados pelo algoritmo são promissores e demonstram uma ótima precisão e aplicabilidade do método proposto. / This work presents a wavelet transform (WT) application to analyze the high frequency transients in a transmission line caused by a fault, with the purpose of determining its accurate location. The WT is very similar to Fourier Transform (FT), with an important difference: it allows the time determination of different frequency components of a signal. This skill allows the detection of the time of the disturbance occurrence, such as fault transients. The traveling waves generated by the fault occurrence appear as superimposed disturbances on the power frequency signals recorded by the relay. By processing these signals using the WT, the propagation time between the fault point and the relay location can be determined. Consequently, the distance of the fault point can be easily calculated. The delineated problem is boarded through the practical implementation of a computational algorithm. In this implementation, the user can choose the location technique to be employee, using data registered in one or both the terminals of the line, according to the necessity and/or availability of the data. In order to evaluate the applicability of the proposed scheme, the simulation of the transmission line in a faulty condition was utilized. This work makes use of a digital simulator of a faulted EHV (Extra High Voltage) transmission lines known as Alternative Transients Program (ATP). A typical transmission line from CESP (Companhia Energética de São Paulo) were utilized. The simulated data obtained was very close to that found in practice. This study takes into account single phase to ground faults, phase-to-phase faults, phase-phase to ground and three phase faults. The data set was composed of various fault situations considering different fault locations, fault resistances and fault inception angles. The influence of the sampled rate used was also verified as well as the mutual coupling in case of double transmission circuits. The test results reached for the algorithm are promising and demonstrate a highly satisfactory degree of accuracy and applicability of the proposed method.

Este trabalho apresenta um estudo sobre transformada Wavelet aplicada à qualidade da energia elétrica com o intuito de detectar, localizar e classificar eventuais distúrbios que ocorrem no sistema elétrico. Inicialmente é apresentada uma introdução sobre qualidade da energia, mostrando fatos, evoluções e explicando o conceito dos principais fenômenos que interferem na qualidade da energia do sistema elétrico brasileiro, devido, principalmente, à grande demanda de aparelhos eletrônicos produzidos atualmente. Em seguida é mostrada uma revisão dos principais métodos e modelos aplicados atualmente no mundo a respeito do assunto. A transformada Wavelet vem como uma grande ajuda nesta área de análise de sinais, já que é capaz de extrair simultaneamente informações de tempo e freqüência, diferentemente da transformada de Fourier. A simulação dos diversos distúrbios ocorridos no sistema foi realizada através do software ATP (Alternative Transients Program), cujas características seguem corretamente um sistema de distribuição real da concessionária CPFL. Os distúrbios de tensão gerados e analisados foram detectados e localizados através da técnica de Análise Multiresolução e, posteriormente, classificados, utilizando para isto o método da Curva de Desvio Padrão / This dissertation presents a study of Wavelet transform applied to power quality in order to detect, locate and classify disturbances that may occur in the power system. Initially an introduction of power quality is presented, showing facts, evolutions and explaining the concept of the main phenomena that interfere the on power quality of the brazilian power system, due to, mainly, a great demand for electronic devices produced nowadays. A revision of the main methods and models currently applied in the world regarding this subject is also show. The Wavelet transform comes as a great support in the area of signal assessment, as it can extract information about time and frequency simultaneously, differently from the Fourier transform. The simulation of the diverse disturbances occurred in the system was accomplished through ATP software (Alternative Transients Program), whose characteristics correctly follow a system of real distribution of CPFL eletric utility. The generated and analyzed voltage disturbances were detected and located by Multiresolution Analysis technique and later classified by the method of the Standard Deviation

As faltas podem ocorrer em diversos componentes de um sistema elétrico de potência, dentre os quais as linhas de transmissão se destacam como elementos susceptíveis. Devido a suas dimensões físicas, ambiente de operação e interconexão com outros sistemas, a localização exata de uma falta em uma linha de transmissão não é trivial dificultando a tarefa das equipes de manutenção para recomposição do fornecimento de energia. Neste contexto, este trabalho apresenta uma metodologia computacional desenvolvida em ambiente MATLAB® para diagnóstico de faltas em linhas de transmissão baseada na análise de transitórios de alta freqüência nas tensões do sistema. A abordagem desenvolvida neste trabalho inicialmente utiliza a equação de Park para achar a tensão zero, direta e em quadratura e posteriormente detectar a ocorrência da falta através do coeficiente de diferenças. Posteriormente, a teoria de ondas viajantes associada à transformada wavelet contínua são utilizadas objetivando determinar a frequência característica do sinal transitório, a qual é relacionada com o local da falta. Para validar o algoritmo de localização proposto foram realizadas diversas simulações de faltas com o programa ATP (Alternative Transient Program) utilizando dados de uma linha aérea real. A efetividade da abordagem proposta foi avaliada considerando a resistência de falta, o ângulo de incidência da falta e a impedância de curto-circuito do sistema. Os resultados promissores demonstraram a aplicabilidade da formulação proposta para localização faltas em linhas de transmissão aéreas utilizando medições oscilográficas digitais de apenas um terminal. / Faults can occur in several components of an electric power system, among which the transmission line stands out. Due to its physical dimensions, operating environment and interconnection systems, the exact transmission line fault location is non-trivial hindering maintenance crew system restoration. In this context, this work presents a computational methodology developed in MATLAB® environment for fault diagnosis on transmission lines based on voltage high frequency transient analysis. Thus, the approach adopted in this work use firstly the Park equations to find the zero, direct and quadrature voltage and then detect the fault occurrence through the difference coefficient. After, the traveling wave theory associated with continuous wavelet transform application is used for determining the characteristic frequency of the transient signal, which is correlated with the fault location. To validate the proposed fault location algorithm, several fault simulations were executed using ATP software using real overhead line data. The proposed fault location scheme performance was evaluated considering the fault resistance, inception fault angle and short-circuit impedance of the system. The promising results demonstrate the applicability of the proposed formulation for fault location in overhead transmission lines, using one terminal digital oscillographic measurement.

Este trabalho tem a finalidade de analisar algumas técnicas de processamento do sinal mioelétrico, de forma a possibilitar uma posterior implementação de um circuito, que reconheça este sinal e apresente como saída um sinal de controle a ser utilizado em sistemas de reabilitação. Foram simuladas e avaliadas três técnicas de filtragem para o sinal mioelétrico, a fim de atenuar a interferência dos principais ruídos que corrompem este sinal. As técnicas avaliadas foram: filtragem digital clássica; cancelamento de ruído adaptativo e reconstrução do sinal por meio das componentes obtidas pela transformada wavelet. Também foi implementado e analisado um sistema simplificado de reconhecimento dos padrões para este sinal, realizado por meio de uma rede neural artificial, em que foi aplicado em sua entrada o próprio sinal mioelétrico e não suas características obtidas por processamentos matemáticos. Diante dos resultados obtidos os canceladores de ruído adaptativos apresentaram melhores resultados com relação às outras técnicas de filtragem. Apesar de não ter sido adequada para a filtragem, a transformada wavelet mostrou-se uma poderosa ferramenta de análise de sinais, em virtude da sua característica multiresolução. A técnica utilizada para reconhecer os padrões do sinal mostrou bons resultados com os sinais analisados. / This work has the purpose to analyze some techniques for myoelectric signal processing, towards a subsequent implementation of a circuit which can recognize this signal and present as output a control signal to be used in rehabilitation systems. Simulation and evaluation of three filtering techniques for the myoelectric signal were done in order to attenuate the main interferences of noises which corrupt this signal. The evaluated techniques were: classic digital filtering; adaptive noise cancelling and the signal reconstruction through the obtained components by the wavelet transform. A simplified system of pattern recognition for this signal also was implemented and analyzed, accomplished through an artificial neural network. The myoelectric signal itself was applied to the input instead of its characteristics obtained by mathematical processing. According to the results obtained the adaptive noise cancelling presented better results in comparison to the other filtering techniques. Despite not being adequate for filtering, the wavelet transform proved to be a powerful tool for signal analysis, by virtue of its multiresolution characteristics. The technique used to recognize the signal patterns has shown good results with the analyzed signals.

Submitted by Renata Lopes (renatasil82@gmail.com) on 2017-04-26T11:21:06Z No. of bitstreams: 1 leandrorodriguesmansosilva.pdf: 2486503 bytes, checksum: f7db682d8ff4382dc706f061419d2a67 (MD5) / Approved for entry into archive by Adriana Oliveira (adriana.oliveira@ufjf.edu.br) on 2017-04-26T12:26:11Z (GMT) No. of bitstreams: 1 leandrorodriguesmansosilva.pdf: 2486503 bytes, checksum: f7db682d8ff4382dc706f061419d2a67 (MD5) / Made available in DSpace on 2017-04-26T12:26:11Z (GMT). No. of bitstreams: 1 leandrorodriguesmansosilva.pdf: 2486503 bytes, checksum: f7db682d8ff4382dc706f061419d2a67 (MD5) Previous issue date: 2016-02-24 / CAPES - Coordenação de Aperfeiçoamento de Pessoal de Nível Superior / O presente trabalho apresenta o desenvolvimento de métodos de compressão e descompressão de sinais elétricos advindos de sistemas de potência. O método de compressão é baseada em três estágios: a Detecção de Novidades; um estágio de Compressão com Perdas, baseado na Transformada Wavelet Discreta; e finalmente, um estágio de Compressão sem Perdas, baseado no algoritmo Lempel-Ziv-Welch. Foi desenvolvido também, um método para a reconstrução dos sinais comprimidos, que é baseado na Transformada Wavelet Inversa, núcleos de Transformada Discreta de Fourier e na frequência estimada do sinal. A parte de compressão utiliza técnicas de processamento digital de sinais em tempo real, e foi desenvolvida de modo a ser implementada em plataforma FPGA, e a parte de descompressão é executada em um software offline. O trabalho apresenta também um estudo de técnicas de representação esparsa de sinais em dicionários redundantes, com o objetivo de avaliar seu desempenho quando aplicadas à compressão de sinais elétricos, e também, a viabilidade de implementá-las em tempo real, substituindo a Transformada Wavelet Discreta, no estágio de Compressão com Perdas no sistema mencionado anteriormente. / The present work presents the development of a method for power systems signal compression and decompression. The compression method is based in three stages: the novelty detection; the Lossy Compression based on the Discrete Wavelet Transform; and a Lossless Compression stage based on Lempel-Ziv-Welch algorithm. A decompression method was also developed to reconstruct the compressed signals, it is based on Inverse Wavelet Transform, Discrete Fourier Transform cores and the estimated frequency of the signal. The compression part uses digital signal processing techniques in real time, and it was developed to be implemented in FPGA platform. The decompression part runs offline in a PC software. This work also presents a study of sparse representation over redundant dictionaries techniques, in order to evaluate its performance when applied to electrical signal compression, and also the feasibility of implementing them in real time, replacing the Wavelet Transform compression stage in the system mentioned above.

Submitted by Renata Lopes (renatasil82@gmail.com) on 2017-05-11T18:00:15Z No. of bitstreams: 1 ederbarbozakapisch.pdf: 4847277 bytes, checksum: 139f0b67e25b637befdb231fd5402b98 (MD5) / Approved for entry into archive by Adriana Oliveira (adriana.oliveira@ufjf.edu.br) on 2017-05-17T15:19:44Z (GMT) No. of bitstreams: 1 ederbarbozakapisch.pdf: 4847277 bytes, checksum: 139f0b67e25b637befdb231fd5402b98 (MD5) / Made available in DSpace on 2017-05-17T15:19:44Z (GMT). No. of bitstreams: 1 ederbarbozakapisch.pdf: 4847277 bytes, checksum: 139f0b67e25b637befdb231fd5402b98 (MD5) Previous issue date: 2015-03-18 / CNPq - Conselho Nacional de Desenvolvimento Científico e Tecnológico / A presente dissertação apresenta a implementação de um Sistema de Detecção e Compressão de Distúrbios Elétricos (SDCDE), com foco nas implementações baseadas em plataforma FPGA (Field-Programmable Gate Array). Inicialmente são abordados os algoritmos de compressão e detecção. Posteriormente são mostradas as sínteses na FPGA e um protótipo desenvolvido para testes. O sistema proposto é voltado para aplicações em Sistemas Elétricos de Potência (SEPs) e prevê a aquisição e o armazenamento dos distúrbios comumente encontrados nesse campo. A partir dos dados armazenados, é possível reconstruir inteiramente o sinal registrado, para possíveis análises de oscilográfia. O processo de compressão passa por três estágios: detecção de novidade, compressão com perdas, utilizando a Transformada Wavelet Discreta (DWT), e a Compressão em termos de bit. Esses três níveis de compressão permitem uma otimização do espaço de memória utilizado e garantem que longos períodos de registros possam ser armazenados em um cartão de memória. A abordagem das sínteses em FPGA visa avaliar, dentre outros fatores, o consumo de recursos de hardware utilizado, através da implementação de um processador embarcado, criado e idealizado para aplicações de Processamento Digital de Sinais (DSP). A partir do protótipo desenvolvido, alguns resultados de sínteses e estudos de casos com testes executados em ambientes reais, são apresentados. / This dissertation presents the implementation of a System of Detection and Compression of Electrical Disturbances (SDCDE), focusing on implementations based on FPGA platform (Field-Programmable Gate Array). Initially are discussed compression and detection algorithms. Subsequently the synthesis in FPGA and a prototype that was developed for testing are shown. The proposed system is aimed at applications in Electric Power Systems (SEPs) and provides for the acquisition and storage of the disturbances commonly found in this field. From the data stored, the recorded signal can be fully reconstructed for possible oscillographic analysis. The compression process involves three stages: novelty detection, lossy compression, using the Discrete Wavelet Transform (DWT), and a bit-level compression. These three levels of compression allow an optimization of used memory space and they ensure that long periods of records can be stored on a memory card. The approach of the synthesis on FPGA aims to evaluate, among other factors, the usage of hardware resources, through the implementation of an embedded processor, created and designed for digital signal processing applications. From the prototype developed, some results of synthesis and case studies with tests performed in real environments are presented.

[pt] Esta dissertação propõe um sistema de controle de uma mão robótica utilizando sinais eletromiográficos de superfície (sEMG). Os sinais sEMG são coletados de três diferentes grupos musculares do antebraço superior: músculo palmar longo, músculo extensor dos dedos, e músculo extensor radial longo do carpo. O objetivo dessa pesquisa é o desenvolvimento de um protótipo de uma prótese robótica para pessoas que apresentam amputação da mão, controlado por uma interface eletromiográfica baseada em inteligência computacional. Este trabalho abrange os seguintes tópicos: posicionamento dos eletrodos para capturar os sinais sEMG, projeto de um sistema de eletromiografia como interface muscular, método de pré processamento de sinais, uso de técnicas de inteligência computacional para a interpretação dos sinais sEMG, projeto da mão robótica, e método de controle utilizado para controlar as posições dos dedos e o controle da força da mão. Nesta dissertação é utilizada a transformada wavelet como método de extração de características nos sinais eletromiográficos, e uma rede neural multicamada como método de classificação de padrões. O modelo proposto apresentou resultados satisfatórios, conseguindo 90,5 por cento de classificação correta dos padrões para o reconhecimento de 6 posturas diferentes da mão, 94,3 por cento para 5 posturas, e 96,25 por cento para 4 posturas. / [en] This thesis proposes the control of a robotic hand system using surface electromyographic signals (sEMG). The sEMG signals are collected from three different muscle groups of the upper forearm: palmaris longus muscle, extensor digitorum communis muscle, and extensor carpi radialis longus muscle. The objective of this research is to develop a prototype of a robotic prosthesis for people with hand amputation, controlled by an electromyographic interface based on computational intelligence. This thesis covers the following topics: positioning of electrodes to capture the sEMG signals, design of an electromyography muscle interface, preprocessing method, use of techniques of computational intelligence for the interpretation of the sEMG signals, design of the robotic hand, and method used to control the positions of the fingers and of the hand grip force. Here, the wavelet transform is used as a feature extraction method in electromyographic signals, and a multi-layer neural network as a pattern classification method. The proposed model obtained satisfactory results, recognizing 90.5 per cent of the positions for 6 different hand patterns, 94.3 per cent for 5, and 96.25 per cent for 4 positions.

The radar transmitter identification problem involves the identification of a specific radar transmitter based on a received pulse. The radar transmitters are of identical make and model. This makes the problem challenging since the differences between radars of identical make and model will be solely due to component tolerances and variation. Radar pulses also vary in time and frequency which means that the problem is non-stationary. Because of this fact, time-frequency representations such as shift-invariant quadratic time-frequency representations (Cohen’s class) and wavelets were used. A model for a radar transmitter was developed. This consisted of an analytical solution to a pulse-forming network and a linear model of an oscillator. Three signal classification algorithms were developed. A signal classifier was developed that used a radially Gaussian Cohen’s class transform. This time-frequency representation was refined to increase the classification accuracy. The classification was performed with a support vector machine classifier. The second signal classifier used a wavelet packet transform to calculate the feature values. The classification was performed using a support vector machine. The third signal classifier also used the wavelet packet transform to calculate the feature values but used a Universum type classifier for classification. This classifier uses signals from the same domain to increase the classification accuracy. The classifiers were compared against each other on a cubic and exponential chirp test problem and the radar transmitter model. The classifier based on the Cohen’s class transform achieved the best classification accuracy. The classifier based on the wavelet packet transform achieved excellent results on an Electroencephalography (EEG) test dataset. The complexity of the wavelet packet classifier is significantly lower than the Cohen’s class classifier. Copyright / Dissertation (MEng)--University of Pretoria, 2010. / Electrical, Electronic and Computer Engineering / unrestricted

Variable Speed Limit (VSL) strategies identify and disseminate dynamic speed limits that are determined to be appropriate based on prevailing traffic conditions, road surface conditions, and weather conditions. This dissertation develops and evaluates a shockwave-based VSL system that uses a heuristic switching logic-based controller with specified thresholds of prevailing traffic flow conditions. The system aims to improve operations and mobility at critical bottlenecks. Before traffic breakdown occurrence, the proposed VSL’s goal is to prevent or postpone breakdown by decreasing the inflow and achieving uniform distribution in speed and flow. After breakdown occurrence, the VSL system aims to dampen traffic congestion by reducing the inflow traffic to the congested area and increasing the bottleneck capacity by deactivating the VSL at the head of the congested area. The shockwave-based VSL system pushes the VSL location upstream as the congested area propagates upstream. In addition to testing the system using infrastructure detector-based data, this dissertation investigates the use of Connected Vehicle trajectory data as input to the shockwave-based VSL system performance. Since the field Connected Vehicle data are not available, as part of this research, Vehicle-to-Infrastructure communication is modeled in the microscopic simulation to obtain individual vehicle trajectories. In this system, wavelet transform is used to analyze aggregated individual vehicles’ speed data to determine the locations of congestion. The currently recommended calibration procedures of simulation models are generally based on the capacity, volume and system-performance values and do not specifically examine traffic breakdown characteristics. However, since the proposed VSL strategies are countermeasures to the impacts of breakdown conditions, considering breakdown characteristics in the calibration procedure is important to have a reliable assessment. Several enhancements were proposed in this study to account for the breakdown characteristics at bottleneck locations in the calibration process. In this dissertation, performance of shockwave-based VSL is compared to VSL systems with different fixed VSL message sign locations utilizing the calibrated microscopic model. The results show that shockwave-based VSL outperforms fixed-location VSL systems, and it can considerably decrease the maximum back of queue and duration of breakdown while increasing the average speed during breakdown.

Une des préoccupations dans le domaine des communications sécurisées est le concept de sécurité de l'information. Aujourd’hui, la réalité a encore prouvé que la communication entre deux parties sur de longues distances a toujours été sujet au risque d'interception. Devant ces contraintes, de nombreux défis et opportunités s’ouvrent pour l'innovation. Afin de pouvoir fournir une communication sécurisée, cela a conduit les chercheurs à développer plusieurs schémas de stéganographie. La stéganographie est l’art de dissimuler un message de manière secrète dans un support anodin. L’objectif de base de la stéganographie est de permettre une communication secrète sans que personne ne puisse soupçonner son existence, le message secret est dissimulé dans un autre appelé medium de couverture qui peut être image, video, texte, audio,…. Cette propriété a motivé les chercheurs à travailler sur ce nouveau champ d’étude dans le but d’élaborer des systèmes de communication secrète résistante à tout type d’attaques. Cependant, de nombreuses techniques ont été développées pour dissimuler un message secret dans le but d’assurer une communication sécurisée. Les contributions majeures de cette thèse sont en premier lieu, de présenter une nouvelle méthode de stéganographie permettant la dissimulation d’un message secret dans un signal de parole. La dissimulation c’est le processus de cacher l’information secrète de façon à la rendre imperceptible pour une partie tierce, sans même pas soupçonner son existence. Cependant, certaines approches ont été étudiées pour aboutir à une méthode de stéganogaraphie robuste. En partant de ce contexte, on s’est intéressé à développer un système de stéganographie capable d’une part de dissimuler la quantité la plus élevée de paramètre tout en gardant la perceptibilité du signal de la parole. D’autre part nous avons opté pour la conception d’un algorithme de stéganographie assez complexe afin d’assurer l’impossibilité d’extraction de l’information secrète dans le cas ou son existence été détecter. En effet, on peut également garantir la robustesse de notre technique de stéganographie à l’aptitude de préservation du message secret face aux tentatives de détection des systèmes de stéganalyse. Notre technique de dissimulation tire son efficacité de l’utilisation de caractéristiques spécifiques aux signaux de parole et àl’imperfection du système auditif humain. Des évaluations comparatives sur des critères objectifs et subjectifs de qualité sont présentées pour plusieurs types de signaux de parole. Les résultats ont révélé l'efficacité du système développé puisque la technique de dissimulation proposée garantit l’imperceptibilité du message secret voire le soupçon de son existence. Dans la suite expérimentale et dans le même cadre de ce travail, la principale application visée par la thèse concerne la transmission de parole sécurisée par un algorithme de stéganographie. Dans ce but il s’est avéré primordial d’utiliser une des techniques de codage afin de tester la robustesse de notre algorithme stéganographique face au processus de codage et de décodage. Les résultats obtenus montrent la possibilité de reconstruction du signal original (contenant des informations secrètes) après codage. Enfin une évaluation de la robustesse de notre technique de stéganographie vis à vis des attaques est faite de façon à optimiser la technique afin d'augmenter le taux de sécurisation. Devant cette nécessité nous avons proposé une nouvelle technique de stéganalyse basée sur les réseaux de neurones AR-TDNN. La technique présentée ici ne permet pas d'extraire l'éventuel message caché, mais simplement de mettre en évidence sa présence. / One of the concerns in the field of secure communication is the concept of information security. Today’s reality is still showing that communication between two parties over long distances has always been subject to interception. Providing secure communication has driven researchers to develop several cryptography schemes. Cryptography methods achieve security in order to make the information unintelligible to guarantee exclusive access for authenticated recipients. Cryptography consists of making the signal look garbled to unauthorized people. Thus, cryptography indicates the existence of a cryptographic communication in progress, which makes eavesdroppers suspect the existence of valuable data. They are thus incited to intercept the transmitted message and to attempt to decipher the secret information. This may be seen as weakness in cryptography schemes. In contrast to cryptography, steganography allows secret communication by camouflaging the secret signal in another signal (named the cover signal), to avoid suspicion. This quality motivated the researchers to work on this burning field to develop schemes ensuring better resistance to hostile attackers. The word steganography is derived from two Greek words: Stego (means cover) and graphy (means writing). The two combined words constitute steganography, which means covert writing, is the art of hiding written communications. Several steganography techniques were used to send message secretly during wars through the territories of enemies. The major contributions of this thesis are the following ones. We propose a new method to secure speech communication using the Discrete Wavelet Transforms (DWT) and the Fast Fourier Transform (FFT). Our method exploits first the high frequencies using a DWT, then exploits the low-pass spectral properties of the speech magnitude spectrum to hide another speech signal in the low-amplitude high-frequencies region of the cover speech signal. The proposed method allows hiding a large amount of secret information while rendering the steganalysis more complex. Comparative evaluation based on objective and subjective criteria is introduced for original speech signal, stego-signal and reconstructed secret speech signal after the hiding process. Experimental simulations on both female and male speakers revealed that our approach is capable of producing a stego speech that is indistinguishable from the cover speech. The receiver is still able to recover an intelligible copy of the secret speech message. We used an LPC10 coder to test the effect of the coding techniques on the stego-speech signals. Experimental results prove the efficiency of the used coding technique since intelligibility of the stego-speech is maintained after the encoding and decoding processes. We also advocate a new steganalysis technique to ensure the robustness of our steganography method. The proposed classifier is called Autoregressive time delay neural network (ARTDNN). The purpose of this steganalysis system is to identify the presence or not of embedded information, and does not actually attempt to extract or decode the hidden data. The low detecting rate prove the robustness of our hiding technique.