Based on Eigenspace-Based (ESB) method, The paper presents a novel beamforming algorithm for the uniform linear array which constructs a special matrix instead of the covariance matrix. The algorithm can overcome the ...
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An algorithm to compress 3D mesh sequences for dynamic objects is proposed in this work. Given an irregular mesh sequence, we construct a semi-regular mesh structure for the first frame and then map it to the subseque...
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The capacity and performance of code division multiple access (CDMA) systems are limited by multiple access interference (MAI) and "nearfar" problem. Space-time multiuer detection combined with adaptive wave...
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With dynamics property and highly parallel mechanism, recurrent neural networks (RNN) can effectively implement blind adaptive multiuser detection at the circuit time constant level. In this paper, the RNN based blind...
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This paper outlines the automatic extraction of features of paintings' art movements such as classicism, impressionism and cubism;and introduces a system developed for the classification and indexing of paintings ...
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We address a problem to reconstruct the original signal with lost data by using FIR synthesis filters in a class of linear-phase perfect reconstruction (PR) oversampled filter banks (FB) called lapped pseudo-orthogona...
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Based on eigenspace-based (ESB) method, the paper presents a beamforming algorithm for the uniform linear array which constructs a special matrix instead of the covariance matrix. The algorithm can overcome the proble...
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ISBN:
(纸本)0780384016
Based on eigenspace-based (ESB) method, the paper presents a beamforming algorithm for the uniform linear array which constructs a special matrix instead of the covariance matrix. The algorithm can overcome the problem that ESB method cannot work in the environment of coherent signals. Compared, with the ESB using Toeplitz (TESB) technique, the new algorithm can work well in low SNR and small sample size. computer simulation results are presented and demonstrate the effectiveness of the proposed method.
A sound source separation technique based on a two-layered bio-inspired spiking neural network and an enhanced gammatone analysis/synthesis filterbank is proposed. One of the two bio-inspired proposed spectral maps (C...
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A sound source separation technique based on a two-layered bio-inspired spiking neural network and an enhanced gammatone analysis/synthesis filterbank is proposed. One of the two bio-inspired proposed spectral maps (Cochleotopic / AMtopic or Cochleotopic / Spectrotopic) is used as a front-end to the neural network depending on the nature of the intruding sound. We show that the use of an FIR gammatone filterbank outperforms the previous results obtained by using an IIR gammatone cochlear filterbank, since the FIR implementation has near-perfect reconstruction ability and the cascade of the analysis and synthesis filterbanks is linear-phase.
The development of more processing demanding video standards on one hand and the popularity of mobile devices such as digital cameras or wireless videophones on the other hand introduce a need of optimization at the p...
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The development of more processing demanding video standards on one hand and the popularity of mobile devices such as digital cameras or wireless videophones on the other hand introduce a need of optimization at the processor level. Reconfigurable systems provide an interesting answer to this problem and several works have explored the possibility of performance and power optimization. The following study focuses on tuning a reconfigurable hardware to the requirements of future media processing, using DSP operators appearing in recent FPGA families as an alternative to the typical ALU based architectures. In this paper, architecture perspectives are proposed with respect to low cost development constraints, backward compatibility, easy coprocessor usage and power / performance enhancement, using a new scalab.e data representation optimized for quality of service (matching pursuit 3D algorithms).
An all-pole modeling technique, Linear Prediction with Low-frequency Emphasis (LPLE), which emphasizes the lower frequency range of speech, is presented. The method is based on first interpreting conventional linear p...
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An all-pole modeling technique, Linear Prediction with Low-frequency Emphasis (LPLE), which emphasizes the lower frequency range of speech, is presented. The method is based on first interpreting conventional linear predictive (LP) analyses of successive prediction orders with parallel structures using the concept of symmetric linear prediction. In these implementations, symmetric linear prediction is preceded by simple pre-filters, which are of either low or high frequency characteristics. Combining those symmetric linear predictors that are not preceded by high-frequency pre-filters yields the LPLE predictor. It is proved that the all-pole filters computed by LPLE are always stable. The results show that the method is well-suited when low-order all-pole models with improved modeling of the lowest formants are needed.
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