Anindya Bijoy Das

A statistical method for automatic detection of seizure and epilepsy in the dual tree complex wavelet transform domain

In this paper, a statistical method for automatic detection of seizure and epilepsy in the dual-tree complex wavelet transform(DT-CWT) domain is proposed. Variances calculated from the EEG signals and their DT-CWT sub-bands are utilized as features in the classifiers such as artificial neural network(ANN) and support vector machine(SVM). Studies are conducted using EEG signals from a publicly available benchmark EEG database to assess the ability of the proposed method for a number of clinically relevant classification scenario which include healthy vs seizure, healthy and non-seizure(inter-ictal) vs seizure(ictal), and finally, ictal vs inter-ictal records. It is shown that the proposed method using SVM performs better than employing ANN. It gives 100% accuracy, sensitivity and specificity; at least the same or better than those corresponding to several existing techniques. In addition, the proposed method is computationally faster than the time-frequency and EMD-based techniques.

Statistical parameters in the dual tree complex wavelet transform domain for the detection of epilepsy and seizure

In this paper, a comprehensive statistical analysis of electroencephalogram (EEG) signals is carried out in the dual tree complex wavelet transform domain using a publicly available EEG database. It is shown that variance and kurtosis can be effective in distinguishing EEG signals at sub-band levels. It is further shown that the parameters of a normal inverse Gaussian probability density function can equally discriminate the EEG signals at sub-band levels. Thus, these statistical quantities may be used to characterize EEG signals and help the researchers in developing improved classifiers for the detection of epilepsy and seizure and building a better understanding of the diverse process of EEG signals.

Design of novel quaternary encoders and decoders

In this work, a novel quaternary algebra has been employed to design quaternary encoders and decoders of any size. Both priority and ordinary encoders has been designed. The priority encoder in this work may have any arbitrary permutation of input priorities; the design procedure is generic and works for any such permutation. Although no work has ever been done regarding arbitrarily large and randomly prioritized priority encoders in quaternary domain, there exist numerous reports on smaller encoders as well as decoders. The design complexity of the present work has been compared with some of such works done earlier and our designs are more favorable in terms of complexity, especially for large encoders and decoders.

On the design of quaternary comparators

Quaternary logic requires a dedicated comparator circuit besides the usual add/sub unit which may not be optimal due to several reasons. In this paper, we have thoroughly discussed various alternative expressions for equality operator which serves as the basis for quaternary comparator. Then we have derived the necessary equations for single qudit comparator and extended it to serial multi qudit comparator. We have also shown the equations and design of single stage parallel comparator where restriction of fan-in is sacrificed for constant speed. We have ended our discussion with the design of a logarithmic stage parallel comparator which can compute the comparator output within log2(n) time delay for n qudits.

Motor imagery movements detection of EEG signals using statistical features in the Dual Tree Complex Wavelet Transform domain

In this paper, a statistical method has been proposed to identify motor imagery left and right hand movements from electroencephalogram (EEG) signals in the Dual Tree Complex Wavelet Transform (DTCWT) domain. The total experiment is carried out with the publicly available benchmark BCI-competition 2003 Graz motor imagery dataset. First, the EEG signals are decomposed into several bands of real and imaginary coefficients, and then, some statistical features like norm entropy and standard deviation have been calculated. From the one way ANOVA analysis, these features have been shown to be promising to distinguish various kinds of EEG signals. Various types of classifiers have been developed to realize the discrimination among the EEG signals. Among various types of classifiers, K-nearest neighbor (KNN)-based classifiers have been shown to provide a good accuracy of 90.36% which is shown to be better than several existing techniques.

Subband correlation for EEG data in the dual tree complex wavelet transform domain for the detection of epilepsy and seizure

In this paper, a comprehensive analysis of electroencephalogram (EEG) signals is carried out in the dual tree complex wavelet transform domain using a publicly available EEG database. It is shown that maximum cross-correlation among the sub-bands along with the absolute values of the corresponding correlation coefficient and co-variance can be effective in distinguishing EEG signals such as seizure and non-seizure. Thus, these quantities may be used to characterize EEG signals to realize the underlying diverse process of EEG recordings and help the researchers in developing improved classifiers for the detection of epilepsy and seizure.

On the design and analysis of quaternary serial and parallel adders

Optimization techniques for decreasing the time and chip area of adder circuits have been thoroughly studied for years mostly in binary logic system. In this paper, we provide the necessary equations required to design a full adder in quaternary logic system. We provide the design of a logarithmic stage parallel adder which can compute the carries within log2(n) time delay for n qudits. At last, we compare the gate delays of full adder and logarithmic stage parallel adder with the help of mathematical expressions.

An Ant Colony Optimization approach to solve the minimum string cover problem

In this paper, we consider the problem of covering a set of strings S with a set of strings C. C is said to cover S if every string in S can be written as a concatenation of a set of strings which are elements of C. We discuss here three different variants of Ant Colony Optimization (ACO) and propose how we can solve the minimum string cover problem using these techniques. Our simulation results show that ACO based approach gives better solution than the existing approximation algorithm for this problem.

Special feature extraction techniques for Bangla speech

This paper describes several feature extraction techniques, which will facilitate Automatic Speech Recognition (ASR) for Bangla speech. These techniques are applied on different sound-packets, which are essentially segments of Bangla speech. The key temporal regions in a sound-packet that contain vital information about the speech signal are identified. Some novel feature extraction methods are developed using the information contained within these key regions. It has been observed that a single feature cannot provide enough information to achieve successful automatic speech recognition; rather a combination of the features can be used effectively to increase the accuracy.

Identification of Highly Variable Supernumerary Chromosome Segments in an Asexual Pathogen

Supernumerary chromosome segments are known to harbor different transposons from their essential counterparts. The aim of this study was to investigate the role of transposons in the origin and evolution of supernumerary segments in the asexual fungal pathogen Fusarium virguliforme. We compared the genomes of 11 isolates comprising six Fusarium species that cause soybean sudden death syndrome (SDS) or bean root rot (BRR), and identified significant levels of genetic variation in A+T-rich repeat blocks of the essential chromosomes and in A+T-neutral regions of the supernumerary segments. The A+T-rich repeat blocks in the essential chromosomes were highly variable between F. virguliforme and non-F. virguliforme isolates, but were scarcely variable between F. virguliforme isolates. The A+T-neutral regions in the supernumerary segments, however, were highly variable between F. virguliforme isolates, with a statistically significant number (21 standard deviations above the mean) of single nucleotide polymorphisms (SNPs). And supernumerary sequence types and rearrangement patterns of some F. virguliforme isolates were present in an isolate of F. cuneirostrum but not in the other F. virguliforme isolates. The most variable and highly expressed region in the supernumerary segments contained an active DNA transposon that was a most conserved match between F. virguliforme and the unrelated fungus Tolypocladium inflatum. This transposon was absent from two of the F. virguliforme isolates. Furthermore, transposons in the supernumerary segments of some F. virguliforme isolates were present in non-F. virguliforme isolates, but were absent from the other F. virguliforme isolates. Two supernumerary P450 enzymes were 43% and 57% identical to their essential counterparts. This study has raised the possibility that transposons generate genetic variation in supernumerary chromosome segments by frequent horizontal transfer within and between closely related species.