the mel frequency cepstral coefficients are the most widely used feature in speech recognition but they are very sensitive to noise. in this paper to achieve a satisfactorily performance in automatic speech recognition (asr) applications we introduce a noise robust new set of mfcc vector estimated through following steps. first, spectral mean normalization is a pre-processing which applies to t...

In this paper, we define a concept of signal matched multirate whitening filter bank which provides an optimum coding gain. This is achieved by whitening the outputs, of the analysis filter bank, within as well as across the channels, by solving a constrained prediction problem. We also present a fast time and order recursive least squares algorithm to obtain the vector output of the proposed a...

For computational efficiency, it is important to utilize model structure in particle filtering. One of the most important cases occurs when there exists a linear Gaussian substructure, which can be efficiently handled by Kalman filters. This is the standard formulation of the Rao-Blackwellized particle filter (RBPF). This contribution suggests an alternative formulation of this wellknown result...

An algorithm for jointly optimizing uniform analysis and synthesis FIR filter banks for a given input power spectral density is proposed. The FIR subband coder is optimized with respect to the minimum block mean square error between the output and the input signals under a bit constraint. The subband quantizers are modeled as additive, signal-independent, white noise sources. Illustrative examp...

Particle filter and Gaussian mixture implementations of random finite set filters have been proposed to tackle the issue of jointly estimating the number of targets and their states. The Gaussian mixture PHD (GM-PHD) filter has a closed-form expression for the PHD for linear and Gaussian target models, and extensions using the extended Kalman filter or unscented Kalman Filter have been develope...

Improving digital images of carbon nanotubes is an important task for characterizing nanotube structures in Nanoscience and Nanotechnology. A two-step algorithm is proposed for enhancing the information of carbon nanotube images, which are obtained by a scanning electron microscopy. In the first step it is carried out the characterization of the intensity profile of the nanotube by using the fi...

Speaker Recognition is the task of identifying an individual from their voice. Typically this task is performed in two consecutive stages: feature extraction and classification. Using a Gaussian Mixture Model (GMM) classifier different filter-bank configurations were compared as feature extraction techniques for speaker recognition. The filter-banks were also compared to the popular Mel-Frequen...

Gabor filter bank has been successfully used for false positive reduction problem and the discrimination of benign and malignant masses in breast cancer detection. However, a generic Gabor filter bank is not adapted to multi-orientation and multi-scale texture micro-patterns present in the regions of interest (ROIs) of mammograms. There are two main optimization concerns: how many filters shoul...

In this paper propose a denoising method for reducing noise in digital images. An efficient RaoBlackwellized Particle Filter (RBPF) with maximum likelihood Estimation approach is used for improving the learning stage of the image structural model and guiding the particles to the most appropriate direction. It increases the efficiency of particle transitions. The proposal distribution is compute...

Oversampled filter banks (OSFB) have been considered for channel coding, since their redundancy can be utilised to permit the detection and correction of channel errors. In this paper, we propose an OSFB based channel coder for a correlated additive Gaussian noise channel, of which the noise covariance matrix is assumed to be known. Based on a suitable factorisation of this matrix, we develop a...