In this paper, a correntropy induced metric (CIM) criterion based set-membership NLMS (SM-NLMS) algorithm is proposed and its derivation is given in detail for estimating a sparse channel identification system. In the proposed algorithm, the CIM is utilized to exploit the sparsity-aware property of the sparse broadband multiple-path channels to achieve a better channel state information (CSI). Moreover, the proposed CIM criterion based SM-NLMS (CIMSM-NLMS) algorithm is carried out by mimicking a modified cost function under a restricted condition of CIM. The channel estimation performance of the proposed CIMSM-NLMS algorithm obtained by computer simulation is provided for appraising a sparse channel. The achieved simulation results reveal that the proposed CIMSM-NLMS algorithm is stable and outperforms the conventional SM-NLMS and sparse NLMS, LMS and SM-NLMS algorithms in terms of both the convergence and steady-state misalignment.

In this paper we are studying the use of two microphones for acoustic feedback cancellation in hearing aids. With the two microphones approach, an additional microphone is employed to provide added information about the signals which is then utilized to obtain an incoming signal estimate. This estimate is removed from the error signal prior to adapting the canceler, thus removing the undesired signal correlation. In this paper, we propose to use orthogonal transforms with the two microphones approach. The discrete Fourier transform and the discrete cosine transform are implemented to transform the adaptive filter signals. Also, a bank of adaptive filters is employed, each adapting to different portions of the spectrum for a finer control of the adaptation process. Simulation results based on real measured feedback paths and speech signals show improved convergence rates and stable solutions.

Acoustic echo cancellation and feedback cancellation systems require robust and computationally efficient adaptive filtering techniques. In this paper, a new affine projection algorithm with intermittent update of the filter coefficients is proposed where the update interval is determined according to the adaptation state. Simulation results show that the proposed algorithm provides improved performance and reduced average computational complexity compared with other similar algorithms for acoustic echo cancellation and acoustic feedback cancellation applications.

In this paper, two proportionate affine projection sign algorithms are introduced. The performance of the proposed algorithms is compared with that of other proportionate affine algorithms under impulsive interference environment of a network echo cancellation system. It is shown that one of the proposed algorithms, termed memory improved proportionate affine projection sign algorithm (MIP-APSA), is the most robust to impulsive interferences and colored inputs. It is proved that MIP-APSA is a good candidate for network echo cancellation, because of its low complexity, good convergence speed and tracking abilities for echo paths with different sparseness measures, and projection orders.

This study is focused on the necessity to improve the performance of the affine projection (AP) algorithm for active noise control (ANC) applications. The proposed algorithms are evaluated regarding their steady‐state behaviour, their convergence speed and their computational complexity. To this end, different strategies recently applied to the AP for channel identification are proposed for multichannel ANC. These strategies are based either on a variable step size, an evolving projection order, or the combination of both strategies. The developed efficient versions of the AP algorithm use the modified filtered‐x structure, which exhibits faster convergence than other filtering schemes. Simulation results show that the proposed approaches exhibit better performance than the conventional AP algorithm and represent a meaningful choice for practical multichannel ANC applications.

In this paper an improved variable forgetting factor recursive least square (IVFF-RLS) algorithm is proposed. The forgetting factor is adjusted according to the square of a time-averaging estimate of the autocorrelation of a priori and a posteriori errors. The proposed algorithm has fast convergence, and robustness against variable background noise, near-end signal variations and echo path change. The simulation results indicate the superior performances of IVFF-RLS when compared to the RLS and VFF-RLS algorithms.

In sparse adaptive filters, the adaptation gain is “proportionately” redistributed among all the coefficients, emphasizing the large ones in order to speed up their convergence. The improved proportionate affine projection algorithm (IPAPA) is a very attractive choice for echo cancellation, since it combines the good convergence features of the affine projection algorithm (APA) and the gain factors of the improved proportionate normalized least-mean-square (IPNLMS) algorithm. Similar to the APA, a matrix inversion is required within the IPAPA. For practical reasons, the matrix needs to be regularized before inversion, i.e., a positive constant is added to the elements of its main diagonal. In this paper, we propose a formula for choosing the regularization parameter of the IPAPA, aiming at attenuating the effects of the noise in the adaptive filter estimate. Simulation results indicate the validity of this approach in both network and acoustic echo cancellation scenarios.

It is well known that the affine projection algorithm (APA) offers a good tradeoff between convergence rate/tracking and computational complexity. Recently, the evolutionary APA (E-APA) with a variable projection order has been proposed. In this paper, we propose a variable step size (VSS) version of the E-APA, called VSS-E-APA. It is shown that the VSS-E-APA is robust to near-end signal variations. Also, it has both a fast convergence speed and a small steady-state error and a much reduced numerical complexity than the VSS-APA.

Proportionate-type affine projection algorithms (PAPAs) are very attractive choices for echo cancellation. These algorithms combine the good features (convergence and tracking) of the affine projection algorithm (APA) and the proportionate idea, which exploits the sparseness character of the echo path in order to further increase their convergence rate. In this paper, we develop a variable step-size (VSS) version of a recently proposed PAPA. The new algorithm achieves a good compromise between fast convergence rate and low misadjustment, but also has a low computational complexity as compared to its classical counterparts.

In this paper, we propose a new multichannel filtered-x affine projection algorithm based on dichotomous coordinate descent (DCD) iterations for active noise control (ANC) systems. It includes a fast recursive filtering procedure with the filter update incorporated in the DCD iterations. It is shown that the proposed algorithm has a lower complexity, and superior convergence properties than the multichannel filtered-x LMS algorithm. Also, it compares favorably to a previously published DCD based algorithm for ANC systems.

The paper presents a new technique of efficient dynamic range compression and shadow compensation for still color images. The proposed method enhances low light areas while preserving the colors and details, without generating visual artifacts. The approach is based on recursive filtering and contrast stretching techniques, driven by statistical measures of the image and implemented under a logarithmic image processing model. The implementation can be used for any image represented in the RGB or YCbCr color spaces.

For feedforward multichannel active noise control (ANC) systems, the use of adaptive finite-impulse response (FIR) filters is a popular solution, and the multichannel filtered-x least-mean-square (FX-LMS) algorithm is the most commonly used algorithm. The drawback of the FX-LMS is the slow convergence speed, especially for broadband multichannel systems. Recently, some fast affine projection algorithms have been introduced for multichannel ANC, as an interesting alternative to the FX-LMS algorithm. They can provide a significantly improved convergence speed at a reasonable additional computational cost. Yet, the additional computational cost or the potential numerical instability in some of the recently proposed algorithms can prevent the use of those algorithms for some applications. In this paper, we propose two pseudo-affine projection algorithms for multichannel ANC: one based on the Gauss-Seidel method and one based on dichotomous coordinate descent (DCD) iterations. It is shown that the proposed algorithms typically have a lower complexity than the previously published fast affine projection algorithms for ANC, with very similar good convergence properties and good numerical stability. Thus, the proposed algorithms are an interesting alternative to the standard FX-LMS algorithm for ANC, providing an improved performance for a computational load of the same order

The paper proposes a robust and stable fast affine projection algorithm based on the Gauss-Seidel method, the so called modified Gauss-Seidel fast affine projection algorithm. The proposed algorithm is generalized for simplified Volterra filters as well. The computational complexity of both the modified Gauss-Seidel fast affine projection algorithm and its generalization for simplified Volterra filters is derived and their performance for acoustic echo cancellation is assessed.

We propose a new approach for real-time implementation of the fast affine projection (FAP) algorithm. This is based on exploiting the recently introduced dichotomous coordinate descent (DCD) algorithm, which is especially efficient for solving systems of linear equations on real-time hardware and software platforms since it is free of multiplication and division. The numerical stability of the DCD algorithm allows the new combined DCD-FAP algorithm also to be stable. The convergence and complexity of the DCD-FAP algorithm is compared with that of the FAP, Gauss-Seidel FAP (GS-FAP), and modified GS-FAP algorithms in the application to acoustic echo cancellation. The DCD-FAP algorithm demonstrates a performance close to that of the FAP algorithm with ideal matrix inversion and the complexity smaller than that of the Gauss-Seidel FAP algorithms.

It is well known that fast affine projection algorithms can produce a good trade-off between convergence speed and computational complexity. In this paper, we propose a new pseudo fast affine projection algorithm based on the Gauss-Seidel scheme for multichannel active noise control (ANC) systems. It is shown that the proposed algorithm has a lower complexity than previously published fast affine projection algorithms, with similar convergence properties and better numerical stability.

In this paper we present several implementations of the Modified A Priori Error-Feedback LSL (EF-LSL) algorithm [1] on the VIRTEX FPGA. Its computational parallelism and pipelinabilty are important advantages. Internally, the computations are based on the logarithmic number system. We compare 32-bit (SINGLE-ALU or DUAL-ALU version) and 20-bit (QUADRI-ALU versions). We show that the LNS implementation can outperform the standard DSP solutions based on 32-bit floating-point processors.