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We propose a novel parallel asynchronous algorithmic framework for the minimization of the sum of a smooth (nonconvex) function and a convex (nonsmooth) regularizer. The framework hinges on Successive Convex Approximation (SCA) techniques and on a novel probabilistic model which describes in a unified way a variety of asynchronous settings in a more faithful and exhaustive way with respect to state-of-the-art...
In this paper, a novel joint recursive least square (RLS) and least mean square (LMS) adaptive equalization algorithm for indoor, short range wireless communications under staircase environment is proposed. In this algorithm, the RLS is initially used to realize the fast convergence. Then, the LMS is adapted to rapidly optimize the receiving signals. Once the imbalance of the equalizer or severe channel...
An Acoustic Echo Canceller (AEC) based on the Decoupled Partitioned Block Frequency Domain Adaptive Filter (DPBFDAF) [3, 4] is implemented on a single Digital Signal Processor (DSP), the TMS320C30. This flexible setup makes it possible to choose the sample frequency (fs), the number of coefficients (N) of the adaptive filter and the processing delay independent of one another (only limited by the...
In this paper, different adaptive algorithms for stereophonic acoustic echo cancellation are compared. The algorithms include the simple LMS algorithm and two specialized two-channel adaptive algorithms. Due to the high calculation complexity needed in stereophonic acoustic echo cancellation applications, the time domain algorithms are applied in a subband structure. The comparison include aspects...
This paper presents a novel Time Domain (TD) based Multiple-Input Multiple Output (MIMO) implementation of the Expectation-Maximization (EM) algorithm. The algorithm is able to achieve Maximum Likelihood (ML) performance with reduced complexity. Results show how performance superior to the Recursive Least Square (RLS) algorithm, in terms of both convergence and residual Mean Squared Error (MSE), can...
<?Pub Dtl?>This paper presents a precise analysis of the critical path of the least-mean-square (LMS) adaptive filter for deriving its architectures for high-speed and low-complexity implementation. It is shown that the direct-form LMS adaptive filter has nearly the same critical path as its transpose-form counterpart, but provides much faster convergence and lower register complexity. From...
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