New Trends in Chaos-Based Communications and Signal Processing
In the last decades many possible applications of nonlinear dynamics in communication systems and... more In the last decades many possible applications of nonlinear dynamics in communication systems and signal processing have been reported. Conversely, techniques usually employed by the signal processing and communication systems communities, as correlation, power spectral density analysis, and linear filters, among others have been used to characterize chaotic dynamical systems. This chapter presents four works that aim to use tools from both fields to generate new and interesting results: (1) a message authentication system based on chaotic fingerprint; (2) a study of the spectral characteristics of the chaotic orbits of the Henon map; (3) an investigation of the chaotic nature of the signals generated by a filtered Henon map, and (4) a communication system that presents equalization and a switching scheme between chaos-based and conventional modulations.
Many communication systems based on the synchronization of chaotic systems have been proposed as ... more Many communication systems based on the synchronization of chaotic systems have been proposed as an alternative spread spectrum modulation that improves the level of privacy in data transmission. However, due to the lack of robustness of complete chaotic synchronization, even minor channel impairments are enough to hinder communication. In this paper, we propose a communication system that includes an adaptive equalizer and a switching scheme to switch between a chaos-based modulation and a conventional one. Preliminary simulation results show that the switching and equalization algorithms can successfully recover the transmitted sequence in different non-ideal scenarios. keywords: Analysis and Control of Nonlinear Dynamical Systems with Practical Applications, Chaos and Global Nonlinear Dynamics, Synchronization in Nonlinear Systems.
In this paper, we propose a sampling mechanism for adaptive diffusion networks that adaptively ch... more In this paper, we propose a sampling mechanism for adaptive diffusion networks that adaptively changes the amount of sampled nodes based on mean-squared error in the neighborhood of each node. It presents fast convergence during transient and a significant reduction in the number of sampled nodes in steady state. Besides reducing the computational cost, the proposed mechanism can also be used as a censoring technique, thus saving energy by reducing the amount of communication between nodes. We also present a theoretical analysis to obtain lower and upper bounds for the number of network nodes sampled in steady state.
2019 27th European Signal Processing Conference (EUSIPCO)
Graph signal processing has attracted attention in the signal processing community, since it is a... more Graph signal processing has attracted attention in the signal processing community, since it is an effective tool to deal with great quantities of interrelated data. Recently, a diffusion algorithm for adaptively learning from streaming graphs signals was proposed. However, it suffers from high computational cost since all nodes in the graph are sampled even in steady state. In this paper, we propose an adaptive sampling method for this solution that allows a reduction in computational cost in steady state, while maintaining convergence rate and presenting a slightly better steady-state performance. We also present an analysis to give insights about proper choices for its adaptation parameters.
Anais de XXXVIII Simpósio Brasileiro de Telecomunicações e Processamento de Sinais
Resumo-A restauração de imagens tem por objetivo atenuar distorções causadas no processo de aquis... more Resumo-A restauração de imagens tem por objetivo atenuar distorções causadas no processo de aquisição. Neste artigo, utiliza-se uma rede neural convolucional residual para restauração de imagens coloridas, degradadas por uma função de espalhamento de ponto gaussiana. Como função custo, foram considerados o erro quadrático médio e uma função do índice de similaridade estrutural (structural similarity-SSIM). Por meio de simulações, verifica-se que os melhores resultados de restauração foram obtidos com a função custo baseada no SSIM. Palavras-Chave-Rede neural convolucional residual, restauração de imagens, função de espalhamento de ponto gaussiana, índice de similaridade estrutural.
Anais de XXXVII Simpósio Brasileiro de Telecomunicações e Processamento de Sinais
Resumo-O processamento de sinais em grafos tem atraído a atenção da comunidade científica por ser... more Resumo-O processamento de sinais em grafos tem atraído a atenção da comunidade científica por ser uma ferramenta interessante para lidar com grandes quantidades de dados interrelacionados. Recentemente, foi proposto um algoritmo difuso para a filtragem adaptativa de sinais sobre grafos. Entretanto, esse algoritmo apresenta um custo computacional elevado, pois todos os nós do grafo são amostrados mesmo em regime permanente. Neste trabalho,é proposto um método adaptativo de amostragem para esse algoritmo que permite uma redução no custo computacional em regime permanente preservando-se o desempenho do algoritmo. Tambémé apresentada uma análise para facilitar a escolha de seus parâmetros. Palavras-Chave-Processamento de sinais em grafos, amostragem em grafos, adaptação difusa, filtragem em grafos, combinações convexas. Abstract-Graph signal processing has attracted attention in the signal processing community, since it is an effective tool to deal with large quantities of interrelated data. Recently, a diffusion algorithm for graph adaptive filtering was proposed. However, it suffers from high computational cost since all nodes in the graph are sampled even in steady state. In this paper, we propose an adaptive sampling method for this solution that reduces the computational cost in steady state, while maintaining convergence rate and steady-state performance. We also present an analysis to give insights about proper choices for its adaptation parameters.
Anais de XXXVI Simpósio Brasileiro de Telecomunicações e Processamento de Sinais
Resumo-Processamento de sinais em grafos tem despertado interesse na comunidade científica, pois ... more Resumo-Processamento de sinais em grafos tem despertado interesse na comunidade científica, pois consiste em uma ferramenta eficiente para representar grandes quantidades de dados inter-relacionados. Encontra aplicações emáreas como redes de comunicação, análise de imagens, estimação de temperatura, etc. Recentemente, foram propostas duas soluções adaptativas para o processamento de sinais em grafos baseadas no algoritmo LMS (least-mean-squares). Neste artigo, elas são revisitadas e comparadas por meio de simulações. Verifica-se que uma delas apresenta maior dificuldade em acompanhar variações do sinal de entrada, o que dificulta a escolha do passo de adaptação.
Anais de XXXVI Simpósio Brasileiro de Telecomunicações e Processamento de Sinais
Resumo-A restauração de imagens busca eliminar as distorções causadas no processo de aquisição. N... more Resumo-A restauração de imagens busca eliminar as distorções causadas no processo de aquisição. Neste artigo, utiliza-se uma rede neuronal MLP (Multilayer Perceptron) para restaurar imagens que contêm quatro tons de cinza e que foram degradadas por uma função gaussiana. Palavras-Chave-Processamento de imagens, restauração de imagens, rede neuronal, aprendizado de máquina.
Chaos-based communication systems have attracted attention of researchers in academy and industry... more Chaos-based communication systems have attracted attention of researchers in academy and industry in the last decades. A particular family of such systems has as basic idea to use the transmitted message to modify a known nonlinear chaotic signal generator (CSG). In the receiver, the knowledge of the employed nonlinear CSG in conjunction with chaotic synchronization permits to recover the original message. These systems are an alternative for spread spectrum communication with a possible increase in the security in the physical layer, since it is necessary to perfectly know the CSG in the receiver to decode the message. However, the lack of robustness of chaotic synchronization in relation to channel noise and intersymbol interference still poses a barrier for their practical use. The problem of equalization for such systems have been tackled for a while, and algorithms based on the normalized least-mean squares have presented auspicious results for linear channels. For nonlinear channels, Kernel Adaptive Filters (KAFs) have been used since they are able to solve nonlinear problems implicitly projecting the input vector into a larger dimension space, where they can be linearly solved. Therefore, in this paper, we propose the use of KAFs with two purposes: to equalize linear and nonlinear channels and, at the same time, decode the message without knowledge of the CSG in the receiver. Simulation results show that the proposed solution is able to perform these tasks.
Many communication systems based on the synchronization of chaotic systems have been proposed as ... more Many communication systems based on the synchronization of chaotic systems have been proposed as an alternative spread spectrum modulation that improves the level of privacy in data transmission. However, due to the lack of robustness of complete chaotic synchronization, even minor channel impairments are enough to hinder communication. In this paper, we propose a communication system that includes an adaptive equalizer and a switching scheme to alter between a chaos-based modulation and a conventional one, depending on the communication channel conditions. Simulation results show that the switching and equalization algorithms can successfully recover the transmitted sequence in different nonideal scenarios. Keywords Analysis and Control of Nonlinear Dynamical Systems with Practical Applications • Chaos and Global Nonlinear Dynamics • Synchronization in Nonlinear Systems.
Distributed signal processing has attracted widespread attention in the scientific community due ... more Distributed signal processing has attracted widespread attention in the scientific community due to its several advantages over centralized approaches. Recently, graph signal processing has risen to prominence, and adaptive distributed solutions have also been proposed in the area. Both in the classical framework and in graph signal processing, sampling and censoring techniques have been topics of intense research, since the cost associated with measuring and/or transmitting data throughout the entire network may be prohibitive in certain applications. In this paper, we propose a low-cost adaptive mechanism for sampling and censoring over diffusion networks that uses information from more nodes when the error in the network is high and from less nodes otherwise. It presents fast convergence during transient and a significant reduction in computational cost and energy consumption in steady state. As a censoring technique, we show that it is able to noticeably outperform other solutio...
2008 42nd Asilomar Conference on Signals, Systems and Computers, 2008
We extend the analysis presented in [1] for the affine combination of two least mean-square (LMS)... more We extend the analysis presented in [1] for the affine combination of two least mean-square (LMS) filters to allow for colored inputs and nonstationary environments. Our theoretical model deals, in a unified way, with any combinations based on the following algorithms: LMS, normalized LMS (NLMS), and recursive-least squares (RLS). Through the analysis, we observe that the affine combination of two algorithms of the same family with close adaptation parameters (stepsizes or forgetting factors) provides a 3 dB gain in relation to its best component filter. We study this behavior in stationary and nonstationary environments. Good agreement between analytical and simulation results is always observed. Furthermore, a simple geometrical interpretation of the affine combination is investigated. A model for the transient and steady-state behavior of two possible algorithms for estimation of the mixing parameter is proposed. The model explains situations in which adaptive combination algorithms may achieve good performance.
ABSTRACT Many communication systems applying synchronism of chaotic systems have been proposed as... more ABSTRACT Many communication systems applying synchronism of chaotic systems have been proposed as an alternative spread spectrum modulation that improves the level of privacy in data transmission. However, due to the lack of robustness of chaos synchronization, even minor channel imperfections are enough to hinder communication. In this paper, we propose an adaptive equalization scheme based on a modified normalized least-mean-squares (NLMS) algorithm, which enables chaotic synchronization when the communication channel is not ideal. As an example of application, this scheme is used to recover a binary sequence modulated by a chaotic signal generated by an Hénon map. Simulation results show that the modified NLMS can successfully equalize the channel in different scenarios.
Ieee Transactions on Signal Processing, Aug 1, 2010
In this paper, we propose an approach to the transient and steady-state analysis of the affine co... more In this paper, we propose an approach to the transient and steady-state analysis of the affine combination of one fast and one slow adaptive filters. The theoretical models are based on expressions for the excess mean-square error (EMSE) and cross-EMSE of the component filters, which allows their application to different combinations of algorithms, such as least mean-squares (LMS), normalized LMS (NLMS), and constant modulus algorithm (CMA), considering white or colored inputs and stationary or nonstationary environments. Since the desired universal behavior of the combination depends on the correct estimation of the mixing parameter at every instant, its adaptation is also taken into account in the transient analysis. Furthermore, we propose normalized algorithms for the adaptation of the mixing parameter that exhibit good performance.
Acoustics Speech and Signal Processing 1988 Icassp 88 1988 International Conference on, 2009
We extend the affine combination of one fast and one slow least meansquare (LMS) filter to blind ... more We extend the affine combination of one fast and one slow least meansquare (LMS) filter to blind equalization, considering the combination of two constant modulus algorithms (CMA). We analyze the proposed combination in stationary and nonstationary environments verifying that there are situations where the absence of the restriction on the mixing parameter can be advantageous for the combination. Furthermore, we propose a combination of two CMAs with different initializations. Preliminary simulations show that this scheme can avoid local minima and eventually can present a faster convergence rate than that of its components.
ABSTRACT Neste artigo, é proposta uma função de codificação para sistemas de comunicação baseados... more ABSTRACT Neste artigo, é proposta uma função de codificação para sistemas de comunicação baseados em caos, que assegura a geração de sinais caóticos. Com base nessa função, é apresentado um esquema de equalização adaptativa. Por meio de resultados de simulação, é mostrado que esse sistema apresenta maior imunidade à interferência intersimbólica e ruı́do.
New Trends in Chaos-Based Communications and Signal Processing
In the last decades many possible applications of nonlinear dynamics in communication systems and... more In the last decades many possible applications of nonlinear dynamics in communication systems and signal processing have been reported. Conversely, techniques usually employed by the signal processing and communication systems communities, as correlation, power spectral density analysis, and linear filters, among others have been used to characterize chaotic dynamical systems. This chapter presents four works that aim to use tools from both fields to generate new and interesting results: (1) a message authentication system based on chaotic fingerprint; (2) a study of the spectral characteristics of the chaotic orbits of the Henon map; (3) an investigation of the chaotic nature of the signals generated by a filtered Henon map, and (4) a communication system that presents equalization and a switching scheme between chaos-based and conventional modulations.
Many communication systems based on the synchronization of chaotic systems have been proposed as ... more Many communication systems based on the synchronization of chaotic systems have been proposed as an alternative spread spectrum modulation that improves the level of privacy in data transmission. However, due to the lack of robustness of complete chaotic synchronization, even minor channel impairments are enough to hinder communication. In this paper, we propose a communication system that includes an adaptive equalizer and a switching scheme to switch between a chaos-based modulation and a conventional one. Preliminary simulation results show that the switching and equalization algorithms can successfully recover the transmitted sequence in different non-ideal scenarios. keywords: Analysis and Control of Nonlinear Dynamical Systems with Practical Applications, Chaos and Global Nonlinear Dynamics, Synchronization in Nonlinear Systems.
In this paper, we propose a sampling mechanism for adaptive diffusion networks that adaptively ch... more In this paper, we propose a sampling mechanism for adaptive diffusion networks that adaptively changes the amount of sampled nodes based on mean-squared error in the neighborhood of each node. It presents fast convergence during transient and a significant reduction in the number of sampled nodes in steady state. Besides reducing the computational cost, the proposed mechanism can also be used as a censoring technique, thus saving energy by reducing the amount of communication between nodes. We also present a theoretical analysis to obtain lower and upper bounds for the number of network nodes sampled in steady state.
2019 27th European Signal Processing Conference (EUSIPCO)
Graph signal processing has attracted attention in the signal processing community, since it is a... more Graph signal processing has attracted attention in the signal processing community, since it is an effective tool to deal with great quantities of interrelated data. Recently, a diffusion algorithm for adaptively learning from streaming graphs signals was proposed. However, it suffers from high computational cost since all nodes in the graph are sampled even in steady state. In this paper, we propose an adaptive sampling method for this solution that allows a reduction in computational cost in steady state, while maintaining convergence rate and presenting a slightly better steady-state performance. We also present an analysis to give insights about proper choices for its adaptation parameters.
Anais de XXXVIII Simpósio Brasileiro de Telecomunicações e Processamento de Sinais
Resumo-A restauração de imagens tem por objetivo atenuar distorções causadas no processo de aquis... more Resumo-A restauração de imagens tem por objetivo atenuar distorções causadas no processo de aquisição. Neste artigo, utiliza-se uma rede neural convolucional residual para restauração de imagens coloridas, degradadas por uma função de espalhamento de ponto gaussiana. Como função custo, foram considerados o erro quadrático médio e uma função do índice de similaridade estrutural (structural similarity-SSIM). Por meio de simulações, verifica-se que os melhores resultados de restauração foram obtidos com a função custo baseada no SSIM. Palavras-Chave-Rede neural convolucional residual, restauração de imagens, função de espalhamento de ponto gaussiana, índice de similaridade estrutural.
Anais de XXXVII Simpósio Brasileiro de Telecomunicações e Processamento de Sinais
Resumo-O processamento de sinais em grafos tem atraído a atenção da comunidade científica por ser... more Resumo-O processamento de sinais em grafos tem atraído a atenção da comunidade científica por ser uma ferramenta interessante para lidar com grandes quantidades de dados interrelacionados. Recentemente, foi proposto um algoritmo difuso para a filtragem adaptativa de sinais sobre grafos. Entretanto, esse algoritmo apresenta um custo computacional elevado, pois todos os nós do grafo são amostrados mesmo em regime permanente. Neste trabalho,é proposto um método adaptativo de amostragem para esse algoritmo que permite uma redução no custo computacional em regime permanente preservando-se o desempenho do algoritmo. Tambémé apresentada uma análise para facilitar a escolha de seus parâmetros. Palavras-Chave-Processamento de sinais em grafos, amostragem em grafos, adaptação difusa, filtragem em grafos, combinações convexas. Abstract-Graph signal processing has attracted attention in the signal processing community, since it is an effective tool to deal with large quantities of interrelated data. Recently, a diffusion algorithm for graph adaptive filtering was proposed. However, it suffers from high computational cost since all nodes in the graph are sampled even in steady state. In this paper, we propose an adaptive sampling method for this solution that reduces the computational cost in steady state, while maintaining convergence rate and steady-state performance. We also present an analysis to give insights about proper choices for its adaptation parameters.
Anais de XXXVI Simpósio Brasileiro de Telecomunicações e Processamento de Sinais
Resumo-Processamento de sinais em grafos tem despertado interesse na comunidade científica, pois ... more Resumo-Processamento de sinais em grafos tem despertado interesse na comunidade científica, pois consiste em uma ferramenta eficiente para representar grandes quantidades de dados inter-relacionados. Encontra aplicações emáreas como redes de comunicação, análise de imagens, estimação de temperatura, etc. Recentemente, foram propostas duas soluções adaptativas para o processamento de sinais em grafos baseadas no algoritmo LMS (least-mean-squares). Neste artigo, elas são revisitadas e comparadas por meio de simulações. Verifica-se que uma delas apresenta maior dificuldade em acompanhar variações do sinal de entrada, o que dificulta a escolha do passo de adaptação.
Anais de XXXVI Simpósio Brasileiro de Telecomunicações e Processamento de Sinais
Resumo-A restauração de imagens busca eliminar as distorções causadas no processo de aquisição. N... more Resumo-A restauração de imagens busca eliminar as distorções causadas no processo de aquisição. Neste artigo, utiliza-se uma rede neuronal MLP (Multilayer Perceptron) para restaurar imagens que contêm quatro tons de cinza e que foram degradadas por uma função gaussiana. Palavras-Chave-Processamento de imagens, restauração de imagens, rede neuronal, aprendizado de máquina.
Chaos-based communication systems have attracted attention of researchers in academy and industry... more Chaos-based communication systems have attracted attention of researchers in academy and industry in the last decades. A particular family of such systems has as basic idea to use the transmitted message to modify a known nonlinear chaotic signal generator (CSG). In the receiver, the knowledge of the employed nonlinear CSG in conjunction with chaotic synchronization permits to recover the original message. These systems are an alternative for spread spectrum communication with a possible increase in the security in the physical layer, since it is necessary to perfectly know the CSG in the receiver to decode the message. However, the lack of robustness of chaotic synchronization in relation to channel noise and intersymbol interference still poses a barrier for their practical use. The problem of equalization for such systems have been tackled for a while, and algorithms based on the normalized least-mean squares have presented auspicious results for linear channels. For nonlinear channels, Kernel Adaptive Filters (KAFs) have been used since they are able to solve nonlinear problems implicitly projecting the input vector into a larger dimension space, where they can be linearly solved. Therefore, in this paper, we propose the use of KAFs with two purposes: to equalize linear and nonlinear channels and, at the same time, decode the message without knowledge of the CSG in the receiver. Simulation results show that the proposed solution is able to perform these tasks.
Many communication systems based on the synchronization of chaotic systems have been proposed as ... more Many communication systems based on the synchronization of chaotic systems have been proposed as an alternative spread spectrum modulation that improves the level of privacy in data transmission. However, due to the lack of robustness of complete chaotic synchronization, even minor channel impairments are enough to hinder communication. In this paper, we propose a communication system that includes an adaptive equalizer and a switching scheme to alter between a chaos-based modulation and a conventional one, depending on the communication channel conditions. Simulation results show that the switching and equalization algorithms can successfully recover the transmitted sequence in different nonideal scenarios. Keywords Analysis and Control of Nonlinear Dynamical Systems with Practical Applications • Chaos and Global Nonlinear Dynamics • Synchronization in Nonlinear Systems.
Distributed signal processing has attracted widespread attention in the scientific community due ... more Distributed signal processing has attracted widespread attention in the scientific community due to its several advantages over centralized approaches. Recently, graph signal processing has risen to prominence, and adaptive distributed solutions have also been proposed in the area. Both in the classical framework and in graph signal processing, sampling and censoring techniques have been topics of intense research, since the cost associated with measuring and/or transmitting data throughout the entire network may be prohibitive in certain applications. In this paper, we propose a low-cost adaptive mechanism for sampling and censoring over diffusion networks that uses information from more nodes when the error in the network is high and from less nodes otherwise. It presents fast convergence during transient and a significant reduction in computational cost and energy consumption in steady state. As a censoring technique, we show that it is able to noticeably outperform other solutio...
2008 42nd Asilomar Conference on Signals, Systems and Computers, 2008
We extend the analysis presented in [1] for the affine combination of two least mean-square (LMS)... more We extend the analysis presented in [1] for the affine combination of two least mean-square (LMS) filters to allow for colored inputs and nonstationary environments. Our theoretical model deals, in a unified way, with any combinations based on the following algorithms: LMS, normalized LMS (NLMS), and recursive-least squares (RLS). Through the analysis, we observe that the affine combination of two algorithms of the same family with close adaptation parameters (stepsizes or forgetting factors) provides a 3 dB gain in relation to its best component filter. We study this behavior in stationary and nonstationary environments. Good agreement between analytical and simulation results is always observed. Furthermore, a simple geometrical interpretation of the affine combination is investigated. A model for the transient and steady-state behavior of two possible algorithms for estimation of the mixing parameter is proposed. The model explains situations in which adaptive combination algorithms may achieve good performance.
ABSTRACT Many communication systems applying synchronism of chaotic systems have been proposed as... more ABSTRACT Many communication systems applying synchronism of chaotic systems have been proposed as an alternative spread spectrum modulation that improves the level of privacy in data transmission. However, due to the lack of robustness of chaos synchronization, even minor channel imperfections are enough to hinder communication. In this paper, we propose an adaptive equalization scheme based on a modified normalized least-mean-squares (NLMS) algorithm, which enables chaotic synchronization when the communication channel is not ideal. As an example of application, this scheme is used to recover a binary sequence modulated by a chaotic signal generated by an Hénon map. Simulation results show that the modified NLMS can successfully equalize the channel in different scenarios.
Ieee Transactions on Signal Processing, Aug 1, 2010
In this paper, we propose an approach to the transient and steady-state analysis of the affine co... more In this paper, we propose an approach to the transient and steady-state analysis of the affine combination of one fast and one slow adaptive filters. The theoretical models are based on expressions for the excess mean-square error (EMSE) and cross-EMSE of the component filters, which allows their application to different combinations of algorithms, such as least mean-squares (LMS), normalized LMS (NLMS), and constant modulus algorithm (CMA), considering white or colored inputs and stationary or nonstationary environments. Since the desired universal behavior of the combination depends on the correct estimation of the mixing parameter at every instant, its adaptation is also taken into account in the transient analysis. Furthermore, we propose normalized algorithms for the adaptation of the mixing parameter that exhibit good performance.
Acoustics Speech and Signal Processing 1988 Icassp 88 1988 International Conference on, 2009
We extend the affine combination of one fast and one slow least meansquare (LMS) filter to blind ... more We extend the affine combination of one fast and one slow least meansquare (LMS) filter to blind equalization, considering the combination of two constant modulus algorithms (CMA). We analyze the proposed combination in stationary and nonstationary environments verifying that there are situations where the absence of the restriction on the mixing parameter can be advantageous for the combination. Furthermore, we propose a combination of two CMAs with different initializations. Preliminary simulations show that this scheme can avoid local minima and eventually can present a faster convergence rate than that of its components.
ABSTRACT Neste artigo, é proposta uma função de codificação para sistemas de comunicação baseados... more ABSTRACT Neste artigo, é proposta uma função de codificação para sistemas de comunicação baseados em caos, que assegura a geração de sinais caóticos. Com base nessa função, é apresentado um esquema de equalização adaptativa. Por meio de resultados de simulação, é mostrado que esse sistema apresenta maior imunidade à interferência intersimbólica e ruı́do.
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