Showing papers by "Palash Kumar Kundu published in 2016"

PID controller design for an interacting tank level process with time delay using MATLAB FOMCON toolbox

Abstract: This paper presents a new way to design PID controller for both integer order and fractional order with a time delay for a typical interacting cylindrical tank system using MATLAB FOMCON toolbox. Here, our work aims to study the performance characteristics of integer order and fractional order PID controller on the current integer order plant obtaining minimum objective function by Nelder — Mead optimization technique with different performance metrics ISE, ITSE and IAE. Next our work shows to make comparison between integer order PID controller based on AMIGO model performance and fractional order PID controller on time domain characteristics. The proposed method aims finally to analyze overall desired performance on fractional order PID controller by adding two extra degrees of freedom over the integer order PID controller with different performance criteria.

Classification of tea samples using SVM as machine learning component of E-tongue

Abstract: This article introduces a new approach for identification of tea sample using pulse voltammetry method in an electronic tongue based instrumentation. The classifier system consists of a principle component (PCA) based feature extraction module followed by support vector machine based discrimination. The PCA score of unknown tea sample is undergone through different pair-wise (binary) classification using SVM for repeated times. For six different categories of tea samples in the present case, unknown sample is examined for fifteen times. The result of classification is six membership grades. Finally these membership grades are analyzed by decision directed acrylic graph method (DDAG) for decision making task about the exact authentication of unknown tea sample belonging to six categories. The proposed method could be equally followed for more than six categories.

Dissimilarity factor based classification of inferior myocardial infarction ECG

Abstract: Electrocardiography (ECG) is popular non-invasive technique for preliminary level investigation on cardiovascular assessment. Computerized analysis of ECG can significantly contribute towards assisted diagnosis and in early detection of many cardiac diseases. Conventional automated ECG classifiers employing soft computing tools may suffer from the inaccuracies that may result in different clinical feature extraction stages. In this paper, we propose the use of a statistical index, namely, dissimilarity factor (D) for classification of normal and Inferior Myocardial Infarction (IMI) data, without the need of any direct clinical feature extraction. Time aligned ECG beats were obtained through filtering, wavelet decomposition processes, followed by PCA based beat enhancement to generate multivariate time series data. The T wave and QRS segments of IMI datasets from Lead II, III and aVF were extracted and compared with corresponding segments of healthy patients using Physionet ptbdb data. With 35 IMI datasets, the average composite dissimilarity factor Dc between normal data was found to be 0.39, and the same between normal and abnormal data were found to be 0.65. This paper shows the promise of descriptive statistical tools as an alternative for medical signal analysis.

Synthesis of ECG waveform using Simulink model

Abstract: Modeling of ECG signal is of much importance as the outcome of it is needed for compression of ECG waveform for remote transmission by wireless link, reconstruction of both normal and abnormal ECG waveform without patient, studying the performance of cardiovascular system or heart. The present work proposes a novel method to design a model of heart according to functions of electrical activity of major parts inside heart. Each individual major part generates potential wave w.r.t. time of its own nature due to depolarization and repolarization processes. The individual potential waves have been modeled using Fourier analysis method. In this paper modeling P-R interval wave, QRS interval wave, S-T interval wave and ECG wave for one cycle using MATLAB Simulink. The proper utilization of MATLAB functions (PR Segment block, QRS Segment block, ST Segment block), MATLAB curve fit GUI-TOOLBOX and MATLAB Simulink tool can lead us to work with ECG signals for processing. The Simulink model major parts have been realized by interval generator blocks, ramp function blocks, product blocks, segment generation blocks and adder thereby generating P-R interval wave, QRS interval wave and S-T interval wave within different time ranges of one cycle of ECG wave. The individuals waves as obtained from PR segment block, QRS segment block, ST segment block are synthesized to produce a typical composite ECG wave.