No description available.

No description available.

Filtros adaptativos com resposta ao impulso infinita (IIR) podem substituir com vantagens aqueles com respostas ao impulso finitas (FIR). Entre estas vantagens está o seu reduzido número de parâmetros que leva a uma menor complexidade computacional na obtenção de respostas similares. Porém, a utilização de filtros adaptativos IIR apresenta alguns problemas práticos, sendo o mais destacado sua convergência lenta. Este problema aparece principalmente quando algoritmos baseados no gradiente são utilizados para a adaptação dos coeficientes do filtro. A abordagem baseada na teoria de realização balanceada de sistemas, previamente utilizada para se analizar filtros com entrada branca, se mostrou uma ferramenta útil para entender o que faz com que um filtro convirja lentamente. Este método já foi aplicado com sucesso na análise de filtros adaptativos IIR com entrada branca nas configurações de identificação e de identificação inversa. Neste trabalho aplicaremos este mesmo método para o caso de entrada não branca. Será mostrado que a configuração de identificação inversa é um caso particular da configuração de identificação com entrada não-branca, podendo ambas serem tratadas conjuntamente. Também será mostrado que o sistema que controla as propriedades de convergência não é mais o sistema desconhecido que se está tentando identificar, e sim um sistema relacionado a este e a densidade espectral da entrada. No caso de entrada branca, esta análise levou ao algoritmo de aproximações sucessivas, o qual, utilizando um bloco auxiliar, tenta fazer com que o filtro adaptativo enxergue um um sistema de rápida convergência. Será apresentada uma generalização deste algoritmo para o caso de entrada não-branca, inclusive serão apontadas limitações do mesmo quanto a valores dos passos de adaptação. Simulações numéricas serão usadas para ilustrar todos os resultados obtidos. / Adaptive filters with infinite impulse response (IIR) can replace with advantages the ones with finite impulse response (FIR). One of these advantages is the reduced number of parameters which leads to a smaller computational complexity giving similar responses. However, the use of adaptive IIR filters has some pratical issue, being the most prominent its slow convergence. This issue is mainly seem when gradient descent algorithms are applied to adptate the filters coefficients. The approach bassed on the balanced realization of systems, previously used to analyze the convergence speed of adaptive IIR filter with white input, has seemed to be a useful tool in understanding what causes the slow convergence in a filter. This approach was sucessful aplliedto the analyzes of the identification and inverse identification configurations. In this work we will aplly this same approach to the non-white input case. It will be shown that the invese identification configuration is a special case of the identification configuration with non-white input, so both can be addressed together. It will also be shown that the convergence properties are no more set by the caracteristics of the unknown system, but by the caracteristics of a system related to it and the input spectral density function. In the white input case, the results of this analysis were used to propose the sucessive approximations algorithm, which uses an auxiliary block trying to make the adaptive filter sees a system with faster convergence. A more general form of this algorithm that includes the non-white input case will be presented, and some drawbacks regarding the adptation stepsize will be pointed out. Numerical simulations will be used to illustrate all the obtained results.

Filtros adaptativos com resposta ao impulso infinita (IIR) podem substituir com vantagens aqueles com respostas ao impulso finitas (FIR). Entre estas vantagens está o seu reduzido número de parâmetros que leva a uma menor complexidade computacional na obtenção de respostas similares. Porém, a utilização de filtros adaptativos IIR apresenta alguns problemas práticos, sendo o mais destacado sua convergência lenta. Este problema aparece principalmente quando algoritmos baseados no gradiente são utilizados para a adaptação dos coeficientes do filtro. A abordagem baseada na teoria de realização balanceada de sistemas, previamente utilizada para se analizar filtros com entrada branca, se mostrou uma ferramenta útil para entender o que faz com que um filtro convirja lentamente. Este método já foi aplicado com sucesso na análise de filtros adaptativos IIR com entrada branca nas configurações de identificação e de identificação inversa. Neste trabalho aplicaremos este mesmo método para o caso de entrada não branca. Será mostrado que a configuração de identificação inversa é um caso particular da configuração de identificação com entrada não-branca, podendo ambas serem tratadas conjuntamente. Também será mostrado que o sistema que controla as propriedades de convergência não é mais o sistema desconhecido que se está tentando identificar, e sim um sistema relacionado a este e a densidade espectral da entrada. No caso de entrada branca, esta análise levou ao algoritmo de aproximações sucessivas, o qual, utilizando um bloco auxiliar, tenta fazer com que o filtro adaptativo enxergue um um sistema de rápida convergência. Será apresentada uma generalização deste algoritmo para o caso de entrada não-branca, inclusive serão apontadas limitações do mesmo quanto a valores dos passos de adaptação. Simulações numéricas serão usadas para ilustrar todos os resultados obtidos. / Adaptive filters with infinite impulse response (IIR) can replace with advantages the ones with finite impulse response (FIR). One of these advantages is the reduced number of parameters which leads to a smaller computational complexity giving similar responses. However, the use of adaptive IIR filters has some pratical issue, being the most prominent its slow convergence. This issue is mainly seem when gradient descent algorithms are applied to adptate the filters coefficients. The approach bassed on the balanced realization of systems, previously used to analyze the convergence speed of adaptive IIR filter with white input, has seemed to be a useful tool in understanding what causes the slow convergence in a filter. This approach was sucessful aplliedto the analyzes of the identification and inverse identification configurations. In this work we will aplly this same approach to the non-white input case. It will be shown that the invese identification configuration is a special case of the identification configuration with non-white input, so both can be addressed together. It will also be shown that the convergence properties are no more set by the caracteristics of the unknown system, but by the caracteristics of a system related to it and the input spectral density function. In the white input case, the results of this analysis were used to propose the sucessive approximations algorithm, which uses an auxiliary block trying to make the adaptive filter sees a system with faster convergence. A more general form of this algorithm that includes the non-white input case will be presented, and some drawbacks regarding the adptation stepsize will be pointed out. Numerical simulations will be used to illustrate all the obtained results.

No description available.

International Telemetering Conference Proceedings / October 21, 2002 / Town & Country Hotel and Conference Center, San Diego, California / FPGAs are increasingly being employed for building real-time signal processing systems. They have been used extensively for implementing the PHY in software radio architectures. This paper provides a technology and market perspective on the use FPGAs for signal processing and demonstrates FPGA DSP using an adaptive channel equalizer case study.

The major application of active noise control (ANC) has been focused on using a single reference signal; the work on multiple reference ANC is very scarce. Here, the behavior of multiple reference ANC is analyzed in both the frequency and time domain, and the coherence functions are provided to evaluate the effectiveness of multiple reference ANC. When there are multiple noise sources, multiple reference sensors are needed to generate complete reference signals. A simplified method combines those signals from multiple reference sensors into a single reference signal. Although this method could result in satisfactory noise control effects under special circumstances, the performance is generally compromised. A widely adopted method feeds each reference signal into a different control filter. This approach suffers from the problem of ill-conditioning when the reference signals are correlated. The problem of ill-conditioning results in slow convergence rate and high sensitivity to measurement error especially when the FXLMS algorithm is applied. To handle this particular problem, the decorrelated Filtered-X LMS (DFXLMS) algorithm is developed and studied in this thesis. Both simulations and experiments have been conducted to verify the DFXLMS algorithm and other issues associated with multiple reference ANC. The results presented herein are consistent with the theoretical analysis, and favorably indicate that the DFXLMS algorithm is effective in improving the convergence speed. To take the maximum advantage of the TMS320C30 DSP board used to implement the controller, several DSP programming issues are discussed, and assembly routines are given in the appendix. Furthermore, a graphical user interface (GUI) running under Windows' environment is introduced. The main purpose of the GUI is to facilitate parameters modification, real time data monitoring and DSP process control. / Master of Science

In recent decades, the wireless communication industry has attracted a great deal of research efforts to satisfy rigorous performance requirements and preserve high spectral efficiency. Along with this trend, I/Q modulation is frequently applied in modern wireless communications to develop high performance and high data rate systems. This has necessitated the need for applying efficient complex-valued signal processing techniques to highly-integrated, multi-standard receiver devices. In this dissertation, novel techniques for complex-valued digital signal enhancement are presented and analyzed for various applications in wireless communications. The first technique is a unified block processing approach to generate the complex-valued conjugate gradient Least Mean Square (LMS) techniques with optimal adaptations. The proposed algorithms exploit the concept of the complex conjugate gradients to find the orthogonal directions for updating the adaptive filter coefficients at each iteration. Along each orthogonal direction, the presented algorithms employ the complex Taylor series expansion to calculate time-varying convergence factors tailored for the adaptive filter coefficients. The performance of the developed technique is tested in the applications of channel estimation, channel equalization, and adaptive array beamforming. Comparing with the state of the art methods, the proposed techniques demonstrate improved performance and exhibit desirable characteristics for practical use. The second complex-valued signal processing technique is a novel Optimal Block Adaptive algorithm based on Circularity, OBA-C. The proposed OBA-C method compensates for a complex imbalanced signal by restoring its circularity. In addition, by utilizing the complex iv Taylor series expansion, the OBA-C method optimally updates the adaptive filter coefficients at each iteration. This algorithm can be applied to mitigate the frequency-dependent I/Q mismatch effects in analog front-end. Simulation results indicate that comparing with the existing methods, OBA-C exhibits superior convergence speed while maintaining excellent accuracy. The third technique is regarding interference rejection in communication systems. The research on both LMS and Independent Component Analysis (ICA) based techniques continues to receive significant attention in the area of interference cancellation. The performance of the LMS and ICA based approaches is studied for signals with different probabilistic distributions. Our research indicates that the ICA-based approach works better for super-Gaussian signals, while the LMS-based method is preferable for sub-Gaussian signals. Therefore, an appropriate choice of interference suppression algorithms can be made to satisfy the ever-increasing demand for better performance in modern receiver design.

During the last decade, the wireless communications industry has grown rapidly. Driven by market demand, service providers are continuously looking for better systems. The main focus of continued research has been to increase the quality of services and system capacity. The Code Division Multiple Access (CDMA) cellular system had been proposed for use as a new standard for cellular telephone systems. A great deal of research has been conducted to develop receiver structures useful for CDMA systems. Traditional receivers such as the correlation and RAKE receivers are vulnerable to the near-far problem, i.e., the problem encountered when one received signal power is stronger than another. This problem is common in mobile environments. For single-user receivers, adaptive filtering techniques can be employed to alleviate multiple access interference and the near-far problem. In this thesis, an adaptive filter receiver is implemented on the FPGA-based configurable computing platform called GigaOps G900. By using FPGAs, designers can implement special-purpose signal processing architectures using specialized data paths, optimized sequencing, and pipelining while still providing some flexibility. This results in better overall system performance, resource utilization, and reduced power consumption. / Master of Science

In hands-free telephony and in teleconference systems, the main aim is to provide agood free voice quality when two or more people communicate from different places.The problem often arises during the conversation is the creation of acoustic echo. Thisproblem will cause the bad quality of voice signal and thus talkers could not hearclearly the content of the conversation, even thought lost the important information.This acoustic echo is actually the noise which is created by the reflection of soundwaves by the wall of the room and the other things exist in the room. The mainobjective for engineers is the cancellation of this acoustic echo and provides an echofree environment for speakers during conversation. For this purpose, scientists designdifferent adaptive filter algorithms. Our thesis is also to study and simulate theacoustics echo cancellation by using different adaptive algorithms.