In this paper, utilization of clustering algorithms for data fusion in decision level is proposed. The results of automatic isolated word recognition, which are derived from speech spectrograph and Linear Predictive Coding (LPC) analysis, are combined with each other by using fuzzy clustering algorithms, especially fuzzy k-means and fuzzy vector quantization. Experimental results show that the...

Storaging or transmission of speech signals at very low bit rate is a hot area in the field of speech processing. We used stochastic inter-frame interpolators and vector quantization (VQ) as a new method for developing a high quality 1200 BPS speech vocoder. The objective and subjecgtive test results show that performance of the new vocoder is compairable with 4800 BPS standard vocoders (as CELP).

In recent years Deep Neural Networks (DNNs) have been rapidly developed in various applications, together with increasingly complex architectures. The performance gain of these DNNs generally comes with high computational costs and large memory consumption, which may not be affordable for mobile platforms. Deep model quantization can be used for reducing the computation and memory costs of DNNs...

This paper studies the optimal bit allocation for shape-gain vector quantization of wireless channels in multiuser (MU) multiple-input multiple-output (MIMO) downlink systems based on linear precoding. Our design minimizes the mean squared-error between the original and quantized channels through optimal bit allocation across shape (direction) and gain (magnitude) for a fixed feedback overhead ...

Hashing is one of the effective techniques for fast Approximate Nearest Neighbour (ANN) search. Traditional single-bit quantization (SBQ) in most hashing methods incurs lots of quantization error which seriously degrades the search performance. To address the limitation of SBQ, researchers have proposed promising multi-bit quantization (MBQ) methods to quantize each projection dimension with mu...

The JPEG image compression method has been widely implemented in digital camera devices. The quantization process plays a primary role in JPEG image compression. The quantization process is used to determine the visibility threshold of the human visual system. The quantization tables are generated from a series psychovisual experiments from several angle points of experimental views. This paper...

The main purpose of this study was to assess the reliability of shape and heterogeneity features in both the PET and the low-dose CT components of PET/CT. A secondary objective was to investigate the impact of image quantization. Methods: A Health Insurance Portability and Accountability Act-compliant secondary analysis of deidentified prospectively acquired PET/CT test-retest datasets of 74 pa...