Showing papers in "Digital Signal Processing in 2008"

TL;DR: A wavelet-based denoising technique for the recovery of signal contaminated by white additive Gaussian noise and a new thresholding procedure is proposed, called subband adaptive, which outperforms the existing thresholding techniques.

TL;DR: The pilot study investigation for any possible electrophysiological activity alterations due to ELF PEMF exposure, was evaluated by the efficiency of DWT as a feature extraction method in representing the signals.

TL;DR: A linear phase FIR filter is designed using particle swarm optimization (PSO) and genetic algorithms (GA) and it is found that the PSO outperforms the GA in some of the presented design cases.

TL;DR: In order to increase the performance of heart sound classification, an incremental neural network is proposed in this study and it is observed that ISOM successfully classifies the HSs even in noisy environment.

TL;DR: The results of applying the proposed method on both synthetic signals and newborn EEGs indicate superiority of the proposed technique over the existing one in reducing noise from signals.

TL;DR: The experimental results show that the proposed method is suitable for various morphologies of ECG data, and that it achieves higher compression ratio with the characteristic features well preserved.

TL;DR: Three-dimensional analyses on inter-carrier interference power (P"I"C"I) reduction methods using a rectangular pulse), a raise-cosine pulse, a ''better-than'' raised- Cosinese pulse, and an improved sinc power pulse are given.

TL;DR: A new technique to eliminate the power line frequency from the electrocardiogram (ECG) signal is proposed and found to be simple to implement in real-time applications and computational complexity is very less compared to any other adaptive techniques.

TL;DR: A technique that has successfully classified arrhythmia from an ECG dataset using a least square support vector machine (LSSVM) is described, suggesting that the proposed method can be used to enhance the performance of a new intelligent assistance diagnosis system.

TL;DR: This work presents a method that uses an algebraic approach to estimate a good starting point to the fixed-point iteration of KPCA for the pre-image problem and shows better performance than the other methods.

TL;DR: This paper finds the optimal horizons and sampling intervals, both in the sense of the minimum mean square error (MSE), for a one-parameter family of the discrete-time unbiased finite impulse response (FIR) filters.

TL;DR: A method for the automatic handwritten signature verification (AHSV) that relies on global features that summarize different aspects of signature shape and dynamics of signature production and shows that the correctness of the algorithm detecting the signature is more acceptable.

TL;DR: An improved spectral subtraction method for reducing acoustic noise added to speech in noisy environments like helicopter cockpit or car engine is proposed and showed a better quality with no distortion for the enhanced speech and the musical noise was effectively masked.

TL;DR: A novel method dedicated to ECG compression that uses the block-based discrete cosine transform and considers the percent root-mean-square difference (PRD) as a controlled quality criterion, and is classified as a valid concurrent to some recently published powerful methods.

TL;DR: A novel approach called WMicaT is introduced that employs an independent component analysis technique in watermark embedding and extraction that is able to extract the watermark without requiring the original image and any information about the watermarks.

TL;DR: A solution based on wavelet packet (WP) is presented and effect of WP on SB values is investigated and WP provides absolutely excellent approximation to required frequency bands and exposes different and impressive SB results.

TL;DR: A generalized form of the well-known least mean square (LMS) filter that incorporates linear time-varying state-space model of the underlying environment is presented and is termed as state- space LMS (SSLMS), resulting in marked improvement in its tracking performance over the standard LMS.

TL;DR: A novel idea to estimate the SNR is introduced and this gives rise to a novel estimated ML (EsML) classifier, in an attempt to reduce the computational complexity of the EML and EsML classifiers, and a simplified minimum distance (MD) classifiers.

TL;DR: A method for designing M-channel cosine-modulated filter banks with prescribed passband ripple, stopband attenuation, and channel overlap based on the minimization of a one-dimensional objective function is proposed.

TL;DR: This paper presents a proper way to reduce the peak-to-average power ratio (PAPR) in Daubechies wavelet-based OFDM (WOFDM) by searching better wavelet packet tree (BWPT) structures by using a brute force search algorithm.

TL;DR: In this paper, the performance of automated diagnostic systems with diverse and composite features for electrocardiogram (ECG) beats was presented and their accuracies were determined, and the classification accuracies of six different classifiers, namely multilayer perceptron neural network, combined neural network (CNN), mixture of experts (ME), modified mixture of expert (MME), probabilistic neural networks (PNN), and support vector machine (SVM), which were trained on diverse or composite features were compared.

TL;DR: A new multichannel filtering approach established on learning-based color morphological operations for impulsive noise removal in color image is presented, which greatly enhances the performance of morphological operation-based filters, especially in the color image highly corrupted by impulsive Noise.

TL;DR: The proposed speech enhancement system provided sufficient noise reduction and good intelligibility and perceptual quality, without causing considerable signal distortion and musical background noise.

TL;DR: The matrix pencil method applies the technique directly to the data to estimate the poles, and works well under the correlated signal case, as opposed to ESPRIT, a statistical subspace based estimation technique, which will work after applying some additional spatial smoothing techniques to tackle the ill conditioning problem of the covariance matrix.

TL;DR: Experimental results indicate that the proposed NFRBAM filter is improvable with the increased fuzzy rules to reduce more noise corrupted images and preserve image details more than SMFAMF.

TL;DR: A new adjustment technique to the standard Haar wavelet is proposed in this paper, by introducing 2n adjusting zeros in the HaarWavelet scaling filter, n being a positive integer, and it is an improvement over the standard mother wavelets for this application.

TL;DR: Simulation results show that the eigenvectors of matrix S better approximate samples of the Hermite-Gaussian functions than those of matrix T and moreover they have a shorter computation time due to the block diagonalization result, which can serve as a better basis for developing the DFRFT.

TL;DR: New blind equalization techniques for QAM signaling are presented, based on the improved square contour algorithm (ISCA), which reduces the misadjustment between transmitted constellation and the new cost function in an efficient manner, which leads to a noteworthy increase in convergence speed and inter symbol interference (ISI) suppression.

TL;DR: An improved method, called riding wave turnover-empirical AM/FM demodulation, is proposed in this paper, which totally eschews the Hilbert transform and can compute the instantaneous frequency of an intrinsic mode function very accurately.

TL;DR: A method to combine signal decomposition with blind signal separation for separating one-dimensional mixed multi-component signal of mechanical watch movement is presented and it is found that the separated source components effectively reveal the insight of the mechanicalwatch movement, and can be used for fault diagnosis.