The role played b y the distortion measure in a vector quant izat ion image encoder is very imporsuch distortion function as long as d ( X , C ) and the centroid of a set of vectors using this distortion function exists. tant. In the following paper we suggest a general class of distor t ion function, the input-dependent weighted square e r r o r distortion, which is computationally simple and ...

Audio compression is designed to reduce the transmission bandwidth requirement of digital audio streams and storage size of audio files. Audio compression has become one of the basic technologies of the multimedia age to achieve transparent coding of audio and speech signals at the lowest possible data rates. This paper presents a comparative analysis of audio signal compression using transform...

We propose a new method for evaluating the mean square error (mse) of a possibly biased estimator 1̂ θ , or, rather, the class of estimators to which it belongs. The method uses confidence intervals c of a corresponding unbiased estimator θ̂ and makes its assessment based on the extent to which c includes 1̂ θ . The method does not require an estimate, implicit or explicit, of the bias of 1̂ θ , is...

Implicit feedback is an approach that utilizes uplink channel state information (CSI) for downlink transmit beamforming on multiple-input multiple-output (MIMO) systems, relying on over-the-air channel reciprocity. The implicit feedback improves throughput efficiency because overhead of CSI feedback for change of over-the-air channel responses is omitted. However, it is necessary for the implic...

The recently proposed low-complexity reduction-bycomposition least-mean-square (LMS) algorithm (RCLMS) costs only half multiplications compared to that of the conventional direct-form LMS algorithm (DLMS). This work intends to characterize its properties and conditions for mean and mean-square convergence. Closed-form mean-square error (MSE) as a function of the LMS step-size and an extra compe...

An optimal mean-square fusion formulas with scalar and matrix weights are presented. The relationship between them is established. The fusion formulas are compared on the continuous-time filtering problem. The basic differential equation for cross-covariance of the local errors being the key quantity for distributed fusion is derived. It is shown that the fusion filters are effective for multi-...

An important theoretical tool in machine learning is the bias/variance decomposition of the generalization error. It was introduced for the mean square error in [3]. The bias/variance decomposition includes the concept of the ave-rage predictor. The bias is the error of the average predictor, and the systematic part of the generalization error, while the variability around the average predictor...

This paper considers the problem of joint synchronization and source localization using time of arrival (TOA) when the known sensor positions and sensor clock biases are subject to random errors. We derive the Cramér-Rao lower bound (CRLB) of the source position and the source clock bias, and quantify the amount of estimation performance degradation due to sensor position errors and sensor cloc...

In this paper, we propose a differential evolution (DE) algorithm for optimizing the placement and power of the pilot tones that are utilized by a least square (LS) algorithm for channel estimation in multipleinput and multiple-output orthogonal frequency-division multiplexing (MIMO-OFDM) systems. Computer simulations demonstrated that the performance of the LS algorithm was increased by optimi...

A blind equalizer attempts to compensate the inter-symbol interference caused by a communication channel without the knowledge of the transmitted sequence. Linear prediction-error lters (PEF) can be used to obtain the equalized symbols. These equalizers are derived assuming a white information sequence. In real communication systems, channel encoding is commonly used to enable the detection and...