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This paper proposes a new adaptation algorithm named Adaptive Step-Size p-Modulo Correlation Phase Algorithm (ASS-pModuloCPhiA) for adaptive filters used in digital QAM systems. The algorithm employs “p-modulus” of the correlation between the error and filter input, and an adaptive step-size control algorithm. The ASS-pModuloCPhiA achieves significant improvement in filter convergence speed of the...
This paper proposes an adaptation algorithm named Recursive Least Normalized Correlation Norms (RLNCN) algorithm for adaptive filters, based on a cost function of a quantity named Normalized Correlation Norm (NCN) which generically yields a family of normalized type algorithms. The RLNCN algorithm achieves a significant improvement in filter convergence speed, while it preserves robustness against...
In order to improve the convergence performance of the LMS filter, transform domain adaptive filters have been widely used. The transformation chosen include Discrete Fourier Transform(DFT), Discrete Sine Transform(DST), Discrete Cosine Transform(DCT) etc. Some comparisons among these transforms, based on their effectiveness in improving convergence of the resulting LMS filter, have also been reported...
In this paper we investigate the steady-state performance of semisupervised regression models adjusted using a modified RLS-like algorithm, identifying the situations where the new algorithm is expected to outperform standard RLS. By using an adaptive combination of the supervised and semisupervised methods, the resulting adaptive filter is guaranteed to perform at least as well as the best contributing...
In this work, we propose an adaptive filter based on a non linear function, namely Recursive Non Linear (RNL) algorithm, which is inspired in the Recursive Lest Square (RLS) algorithm. We derive equations based on a nonlinear function in order to obtain criterions that guarantee convergence. We also make a study about the covariance of the weight vector on steady state and determine equations that...
Infrared image processing has been the focal point of considerable research activity in the last decade mainly because of its wide application areas in security and defense. With the aid of an existing image enhancement technique, Adaptive Unsharp Masking (AUM), proposed optimum parameters selection procedure delivers better performance in sharpness and contrast adjustment for the detection of targets...
In repeaters in wireless cellular networks, feedback signals from the service antennas to the receiving antennas may cause oscillation so that they break the system operations. For predictive elimination of feedback signals, an interference cancellation method employing LMS (Least Mean Square) filter is proposed. The feedback signals to the input antenna removes the feedback signals using the auto-correlation...
The conventional algorithms in the echo canceling system have drawback when they are faced with double-talk condition in noisy environment. Since the double-talk and noise signal are exist, then the error signal is contaminated to estimate the gradient correctly. In this paper, we define a new adaptive algorithm for tap adaptations, based on the correlation function processing, which is called Extended...
A simple and attractive way to reduce the hardware complexity and power consumption of an adaptive filter is to implement it using a partial-update technique whereby only a subset of the adaptive filter coefficients are updated at each iteration. For certain cyclostationary or periodic input signals partial-update techniques become susceptible to divergence problems unlike their full-update counterparts...
Echo path estimation in echo canceling for teleconference system is a problem in double-talk condition. The correlation function based algorithms were defined by the authors to solve this problem. In this paper, in order to improve the convergence speed of correlation function based algorithm, we propose a new modified proportionate step-size adaptation method, and then implement it into frequency...
Usual methods for the development of adaptive filters are based on a stochastic approximation of the gradient vector and Hessian matrix, or on a deterministic minimization of quadratic a posteriori output errors. Gradient-based algorithms are usually placed in the first group, whereas least squares (LS) based algorithms are placed in the second group. These are just how algorithms are usually presented...
Echo path estimation in echo canceling for teleconference system is a problem in double-talk condition. The correlation function based algorithms were defined by the authors to solve this problem. In this paper, in order to improve the convergence speed of correlation function based algorithm, we propose a new modified proportionate step-size adaptation method, and then implement it into frequency...
Stereophonic acoustic echo cancellers (SAEC) have problems more severe than monophonic echo cancellers. The most important problem is the misalignment, which is the mismatch between the impulse responses of adaptive filters and those of the acoustic paths of the receiving room (in the teleconferencing application, as an example) and therefore a severe divergence of filters in the event of abrupt changes...
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