The Experts below are selected from a list of 86655 Experts worldwide ranked by ideXlab platform
Sang Woo Kim - One of the best experts on this subject based on the ideXlab platform.
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fast communication comments on stereo echo cancellation algorithm using adaptive update on the basis of enhanced input Signal Vector
Signal Processing, 2008Co-Authors: Chang Woo Lee, Hyeonwoo Cho, Sang Woo KimAbstract:In the paper ''Stereo echo cancellation algorithm using adaptive update on the basis of enhanced input-Signal Vector'', an enhanced form of the normalized least mean squares (NLMS) algorithm has been proposed. However, the enhanced algorithm has been derived by simply replacing the increment Vector of the conventional NLMS with a new increment Vector while not explicitly defining and validating the cost function of the algorithm. In this letter, we present the cost function of the algorithm, and prove that the algorithm is not a general LMS-type algorithm in some criterion.
Shoji Makino - One of the best experts on this subject based on the ideXlab platform.
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Stereo echo cancellation algorithm using adaptive update on the basis of enhanced input-Signal Vector
Signal Processing, 2006Co-Authors: Satoru Emura, Y. Haneda, Akitoshi Kataoka, Shoji MakinoAbstract:Stereo echo cancellation requires a fast converging adaptive algorithm because the stereo input Signals are highly cross correlated and the convergence rate of the misalignment is slow even after preprocessing for unique identification of stereo echo paths. To speed up the convergence, we propose enhancing the contribution of the decorrelated components in the preprocessed input-Signal Vector to adaptive updates. The adaptive filter coefficients are updated on the basis of either a single or multiple past enhanced input-Signal Vectors.For a single-Vector update, we show how this enhancement improves the convergence rate by analyzing the behavior of the filter coefficient error in the mean. For a two-past-Vector update, simulation showed that the proposed enhancement leads to a faster decrease in misalignment than the corresponding conventional second-order affine projection algorithm while computational complexities are almost the same.
Teng Joon Lim - One of the best experts on this subject based on the ideXlab platform.
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a matrix algebraic approach to successive interference cancellation in cdma
IEEE Transactions on Communications, 2000Co-Authors: Lars K Rasmussen, Teng Joon Lim, A L JohanssonAbstract:In this paper, we describe linear successive interference cancellation (SIC) based on matrix-algebra. We show that linear SIC schemes (single stage and multistage) correspond to linear matrix filtering that can be performed directly on the received chip-matched filtered Signal Vector without explicitly performing the interference cancellation. This leads to an analytical expression for calculating the resulting bit-error rate which is of particular use for short code systems. Convergence issues are discussed, and the concept of /spl epsiv/-convergence is introduced to determine the number of stages required for practical convergence for both short and long codes.
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a matrix algebraic approach to linear parallel interference cancellation in cdma
IEEE Transactions on Communications, 2000Co-Authors: Dongning Guo, Lars K Rasmussen, Sumei Sun, Teng Joon LimAbstract:Linear parallel interference cancellation (PIC) schemes are described and analyzed using matrix algebra. It is shown that the linear PIC, whether conventional or weighted, can be seen as a linear matrix filter applied directly to the chip-matched filtered received Signal Vector. An expression for the exact bit-error rate (BER) is obtained, and conditions on the eigenvalues of the code correlation matrix and the weighting factors to ensure convergence are derived. The close relationship between the linear multistage PIC and the steepest descent method (SDM) for minimizing the mean squared error (MSE) is demonstrated. A modified weighted PIC structure that resembles the SDM is suggested which approaches the minimum MSE (MMSE) detector rather than the decorrelator. It is shown that for a K-user system, only K PIC stages are required for the equivalent matrix filter to be identical to the the MMSE filter. For fewer stages, techniques are devised for optimizing the choice of weights with respect to the MSE. One unique optimal choice of weights is found, which will lead to the minimum achievable MSE at the final stage. Simulation results show that a few stages are sufficient for near-MMSE performance.
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mmse based linear parallel interference cancellation in cdma
International Symposium on Spread Spectrum Techniques and Applications, 1998Co-Authors: Dongning Guo, Lars K Rasmussen, Teng Joon Lim, Sumei Sun, C CheahAbstract:We mathematically describe the linear parallel interference canceller (PIC) using matrix algebra. It is shown that the linear PIC, whether conventional or weighted, can be seen as a linear matrix filter applied directly to the received chip-matched filtered Signal Vector. It is then possible to get an analytical expression for the exact bit error rate and to derive necessary conditions on the eigenvalues of the code correlation matrix and the weighting factors to ensure convergence. The close relationship between the steepest descent method for minimising the mean squared error (MSE) and linear PIC is demonstrated and a modified PIC structure is suggested which converges to the PMMSE detector rather than the decorrelator. Following the principles of the steepest descent method techniques are devised for optimising the choice of weighting factors with respect to the mean squared error. It is shown that only K (the number of users) PIC stages are required for the equivalent matrix filter to be identical to the MMSE filter. For fewer stages, m
Dmitri B Strukov - One of the best experts on this subject based on the ideXlab platform.
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energy efficient moderate precision time domain mixed Signal Vector by matrix multiplier exploiting 1t 1r arrays
IEEE Journal on Exploratory Solid-State Computational Devices and Circuits, 2020Co-Authors: Shubham Sahay, Mohammad Bavandpour, Mohammad Reza Mahmoodi, Dmitri B StrukovAbstract:The emerging mobile devices in the era of Internet-of-Things (IoT) require a dedicated processor to enable computationally intensive applications such as neuromorphic computing and Signal processing. Vector-by-matrix multiplication is the most prominent operation in these applications. Therefore, there is a critical need for compact and ultralow-power Vector-by-matrix multiplier (VMM) blocks to perform resource-intensive low-to-moderate precision computations. To this end, in this article, we propose a time-domain mixed-Signal VMM exploiting a modified configuration of 1MOSFET-1RRAM (1T-1R) array. The proposed VMM overcomes the energy inefficiency of the current-mode VMM approaches based on RRAMs. A rigorous analysis of different nonideal factors affecting the computational precision indicates that the nonnegligible minimum cell currents, channel length modulation (CLM), and drain-induced barrier lowering (DIBL) are the dominant mechanisms degrading the precision of the proposed VMM. We also show that there exists a tradeoff between the computational precision, dynamic range, and the area- and energy-efficiency of the proposed VMM approach. Therefore, we provide the necessary design guidelines for optimizing the performance. Our preliminary results indicate that an effective computational precision of 6 bits is achievable owing to the inherent compensation effect in the modified 1T-1R blocks. Furthermore, a 4-bit $200\times200$ VMM utilizing the proposed approach exhibits a significantly high energy efficiency of ~1.5 Pops/J and a throughput of 2.5 Tops/s including the contribution from the input/output (I/O) circuitry.
Dongning Guo - One of the best experts on this subject based on the ideXlab platform.
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Vector precoding in wireless communications a replica symmetric analysis
Performance Evaluation Methodolgies and Tools, 2007Co-Authors: Ralf R Muller, Dongning Guo, Aris L MoustakasAbstract:We apply the replica method to analyze Vector pre-coding, a method to reduce transmit power in antenna array communications, in the limit of an infinite number of dimensions of the Signal Vector. The analysis applies to a very general class of channel matrices. The statistics of the channel matrix enter the transmitted energy per symbol via its R-transform.
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Vector precoding in high dimensions a replica analysis
International Symposium on Information Theory, 2007Co-Authors: Ralf R Muller, Dongning Guo, Aris L MoustakasAbstract:We apply the replica method to analyze Vector pre-coding, a method to reduce transmit power in antenna array communications, in the limit of an infinite number of dimensions of the Signal Vector. The analysis applies to a very general class of channel matrices. The statistics of the channel matrix enter the transmitted energy per symbol via its R-transform. We specialize our result to inversion of an i.i.d. channel and two cases of Signal point optimization (i) 2-point lattice pre-coding and (ii) compact relaxation. In the two cases the replica symmetric transmitted energy is found to be 4.3 dB and 9.6 dB above the orthogonal case for a square channel matrix, respectively.
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a matrix algebraic approach to linear parallel interference cancellation in cdma
IEEE Transactions on Communications, 2000Co-Authors: Dongning Guo, Lars K Rasmussen, Sumei Sun, Teng Joon LimAbstract:Linear parallel interference cancellation (PIC) schemes are described and analyzed using matrix algebra. It is shown that the linear PIC, whether conventional or weighted, can be seen as a linear matrix filter applied directly to the chip-matched filtered received Signal Vector. An expression for the exact bit-error rate (BER) is obtained, and conditions on the eigenvalues of the code correlation matrix and the weighting factors to ensure convergence are derived. The close relationship between the linear multistage PIC and the steepest descent method (SDM) for minimizing the mean squared error (MSE) is demonstrated. A modified weighted PIC structure that resembles the SDM is suggested which approaches the minimum MSE (MMSE) detector rather than the decorrelator. It is shown that for a K-user system, only K PIC stages are required for the equivalent matrix filter to be identical to the the MMSE filter. For fewer stages, techniques are devised for optimizing the choice of weights with respect to the MSE. One unique optimal choice of weights is found, which will lead to the minimum achievable MSE at the final stage. Simulation results show that a few stages are sufficient for near-MMSE performance.
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mmse based linear parallel interference cancellation in cdma
International Symposium on Spread Spectrum Techniques and Applications, 1998Co-Authors: Dongning Guo, Lars K Rasmussen, Teng Joon Lim, Sumei Sun, C CheahAbstract:We mathematically describe the linear parallel interference canceller (PIC) using matrix algebra. It is shown that the linear PIC, whether conventional or weighted, can be seen as a linear matrix filter applied directly to the received chip-matched filtered Signal Vector. It is then possible to get an analytical expression for the exact bit error rate and to derive necessary conditions on the eigenvalues of the code correlation matrix and the weighting factors to ensure convergence. The close relationship between the steepest descent method for minimising the mean squared error (MSE) and linear PIC is demonstrated and a modified PIC structure is suggested which converges to the PMMSE detector rather than the decorrelator. Following the principles of the steepest descent method techniques are devised for optimising the choice of weighting factors with respect to the mean squared error. It is shown that only K (the number of users) PIC stages are required for the equivalent matrix filter to be identical to the MMSE filter. For fewer stages, m
