Proportionate Affine Projection Sign Algorithm Research Articles

Variable-Step-Size Efficient Proportionate Affine Projection Sign Algorithms

For sparse system identification, a memory-improved proportionate affine projection sign algorithm with a simplified, generalized correntropy induced metric (SGCI-M-IPAPSA) has good filtering performance. However, the SGCI-M-IPAPSA is based on a fixed step size and is not always the best choice. To overcome the limitation of a fixed step size in filtering precision and convergence speed under non-Gaussian impulsive interferences, in this paper, we apply the combined-step-size idea and a variable-step-size method based on the mean-square deviation to the SGCI-M-IPAPSA, respectively, and propose two new robust algorithms to enhance the filtering performance of the SGCI-M-IPAPSA. In addition, by combining the combined-step-size and proposed variable-step-size methods, we propose a fresh combined variable-step-size way and apply it to the SGCI-M-IPAPSA. The convergence of the proposed algorithms is also elaborated, and a conditional decision on the mean-square error is used to cope with abrupt changes. The better performances of the proposed algorithms than the conventional SGCI-M-IPAPSA in terms of the filtering accuracy and convergence rate are demonstrated with non-Gaussian impulsive interferences for sparse system identification, abrupt changes and colored inputs.

Grid-Tied Distribution Static Synchronous Compensator for Power Quality Enhancement Using Combined-Step-Size Real-Coefficient Improved Proportionate Affine Projection Sign Algorithm

A control structure design of a three-phase three-leg four-wire grid-tied Distribution Static Synchronous Compensator (DSTATCOM) based on a combined-step-size real-coefficient improved proportionate affine projection sign algorithm (CSS-RIP-APSA) has been presented. The three-phase four-wire DSTATCOM is used for reactive power compensation along with harmonic current minimization. This strategy also helps in load balancing and neutral current compensation. The affine projection sign algorithm (APSA) is a member of the adaptive filter family, which has a slow convergence rate. The conventional adaptive filter deals with the trade-off between the convergence rate and the steady-state error. In the proposed algorithm, the RIP-APSA adaptive filter with two different step sizes has been designed to decrease the computational burden while achieving the advantages of a fast convergence rate and reduced steady-state error. The proposed controller also makes the inverter function a shunt compensator. The controller primarily evaluates the fundamental weight component of distorted load currents. The aim of the proposed system is to compensate for reactive power and to ensure unity power factor during the faulty conditions as well as for unbalancing grid conditions. The proposed control algorithm of the grid-tied DSTATCOM works effectively on the laboratory prototype as verified from the experimental results.

Generalized Correntropy Induced Metric Memory-Improved Proportionate Affine Projection Sign Algorithm and Its Combination

In this brief, an efficient memory-improved proportionate affine projection sign algorithm with the generalized correntropy induced metric (GCI-M-IP-APSA) is proposed to modify the filtering performance for sparse system identification. In addition, a simplified implementation of GCI-M-IP-APSA is derived, and called as SGCI-M-IP-APSA, which has lower computational complexity and realizes comparable filtering performances with that of GCI-M-IP-APSA. However, the major limitation of proposed APSA-type algorithm is a poor convergence behavior in non-stationary situations. To overcome such issue, a convex combination method is applied to SGCI-M-IP-APSA to enhance the tracking performance. The good performances of proposed algorithms are verified in sparse system identifications with impulsive noise and abrupt changes.

Modified memory‐improved proportionate affine projection sign algorithm based on correntropy induced metric for sparse system identification

A novel memory-improved proportionate affine projection sign algorithm with correntropy induced metric (CIM-MIP-APSA) is proposed to enhance the filtering performance for sparse system identification. Furthermore, a simplified implementation of the CIM-MIP-APSA (SCIM-MIP-APSA) with low computational complexity is proposed while improving the convergence performance and filtering accuracy. Simulation results demonstrate that the CIM-MIP-APSA and SCIM-MIP-APSA algorithms outperform the existing works for sparse system identification.

Block sparse memory improved proportionate affine projection sign algorithm

A block sparse memory improved proportionate affine projection sign algorithm (BS-MIP-APSA) is proposed for block sparse system identification under impulsive noise. The new BS-MIP-APSA not only inherits the performance improvement for block-sparse system identification, but also achieves robustness to impulsive noise and the efficiency of the memory improved proportionate affine projection sign algorithm (MIP-APSA). Simulations indicate that it can provide both faster convergence rate and better tracking ability under impulsive interference for block sparse system identification as compared to APSA and MIP-APSA.

Sparseness-Controlled Proportionate Affine Projection Sign Algorithms for Acoustic Echo Cancellation

In order to reduce the steady-state misalignment of real-coefficient proportionate affine projection sign algorithm (RP-APSA) for sparse impulse responses, a memory RP-APSA is proposed in this paper by exploiting the historical values of proportionate factors, called MP-APSA. Further, to improve the robustness of MP-APSA and the recently proposed memory-improved RP-APSA (MIP-APSA) for impulse responses with mutative sparseness, two sparseness-controlled algorithms (SC-MP-APSA and SC-MIP-APSA) are developed by estimating the sparseness of the impulse response at each iteration. Simulation results in the context of acoustic echo cancellation show that the proposed algorithms retain good robustness against impulsive interferences. More importantly, the proposed sparseness-controlled algorithms can not only obtain low steady-state misalignment in both the sparse and dispersive situations, but also adapt to the variations in the sparseness of the impulse response.

Memory improved proportionate affine projection sign algorithm

A new proportionate affine projection sign algorithm is proposed for network echo cancellation. It uses a recursive procedure and takes into account the previously computed proportionate coefficients. It is shown that the proposed algorithm can obtain a lower steady-state misalignment than other affine projection sign algorithms for different echo paths, impulsive interferences and step sizes.