Department of Electrical Engineering

Indian Institute of Technology Palakkad&nbsp;(IIT Palakkad or IIT PKD) is a public autonomous&nbsp;engineering&nbsp;and&nbsp;research&nbsp;institute located in&nbsp;Palakkad,&nbsp;Kerala. It was&nbsp;one of the five new&nbsp;IITs&nbsp;proposed in the&nbsp;2014 Union budget of India. The campus was inaugurated on 3 August 2015. The institute has 94 faculty, 978 students, and 63 non-teaching staffs.

IT Palakkad currently offers four-year Bachelor of Technology (B.Tech) and two years MS programmes in 8 different engineering disciplines including&nbsp;Computer Science, Electrical, Mechanical, Civil among others.

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IIT Palakkad

Reduced feedback schemes play a critical role in orthogonal frequency division multiplexing-based cellular systems because they facilitate scheduling and rate adaptation by the base station (BS) while reducing the number of subchannels for which channel state information is fed back by the users. We address the problem of reliable transmission even on subchannels that are fed back by a few users due to feedback constraints. For the practically relevant best-$M$ feedback scheme, in which each user reports only its $M$ strongest subchannels to the BS, we derive a nonlinear constrained minimum mean square error estimator that enables the BS to estimate the signal-to-noise-ratios of all the subchannels of every user. We then propose two lower computational complexity approaches that incur a negligible loss in performance. The novelty of these approaches lies in their exploitation of the structure of the best-$M$ feedback information and the correlation among subchannel gains. Applications to general channel models and to quantized feedback are also shown. In terms of system-level impact, the proposed approaches improve the cell throughput compared to several conventional approaches - without requiring any additional feedback - for uncorrelated and correlated subchannels, and for various schedulers. © 2002-2012 IEEE.

World University root node

IEEE Transactions on Wireless Communications

Best-M feedback in OFDM: Base-station-side estimation and system implications

A novel Dual-Slope Resistance-to-Digital Converter (DSRDC) suitable for single element resistive sensors is presented in this paper. The digital output of the converter is directly proportional to the measurand and is insensitive to the nominal value of resistance, Ro, of the sensor. The choice of fixed resistance employed in a typical DSRDC has been made to be independent of Ro and the constraints on its accuracy have been relaxed. This makes the Resistance-to-Digital Converter versatile, in a manner that it can be easily interfaced with a wide range of resistive sensors having different values of Ro. This task was accomplished by employing an automatic calibration technique, wherein, the reference voltage is digitally adjusted by a Switched Capacitor Controlled Voltage Source (SCCVS). A prototype DSRDC was developed and tested against various values of Ro, which were in-turn emulated using known resistances of values ranging from 25 kü to 200 kü. The worst case error in reading was observed to be less than 0.65 %. © 2016 IEEE.

SAS 2016 - Sensors Applications Symposium, Proceedings

A modified RDC with an auto-adjustable SC source enabled auto-calibration scheme

A receding horizon control of discrete-time Markov jump linear systems with additive Gaussian measurement and process noise, and stochastic constraints is addressed. Given the availability of the underlying jump parameter, recursive equations for optimal state estimation that resemble Kalman filter equations are provided. The receding horizon control law is considered in state-feedback form. Under some detectability conditions, the overall system is pre-stabilized off-line with state-feedback gains by ensuring mean square boundedness of system states. Using a Gaussian assumption, the stochastic constraints are reposed and approximated the original problem as a tractable deterministic receding horizon control problem in terms of conditional means and covariances of the state variable, and solved it on-line with control offset terms. The overall approach is applied on a vertical take-off and landing vehicle dynamical system example. © 2016 IEEE.

Conference on Control and Fault-Tolerant Systems, SysTol

A receding horizon control of Markov jump linear systems with imperfect state information and probabilistic state constraints

Inverter dead-Time, which is meant for safe commutation of devices is known to induce sub-harmonic oscillations in lightly-loaded induction motor drives operating in open-loop. This paper presents an experimental procedure to determine whether a given motor drive would exhibit such oscillations, and if yes, the region of such oscillatory behaviour. In particular, this paper presents case studies on oscillations on account of dead-Time in inverter-fed 5-HP and 10-HP induction motor drives. Experimental measurements are made at different fundamental frequencies and different flux levels (or V/f ratios) to identify if the motor drive exhibits oscillatory behaviour at these various operating points. The regions of oscillatory behaviour of the two motors under no-load are identified experimentally in terms of applied voltage and modulating frequency. A simple dead-Time compensation scheme is employed to mitigate these low-frequency oscillations. The experimental waveforms and corresponding Fast Fourier Transform (FFT) analysis of the motor currents demonstrate the sub-harmonic oscillations and their mitigation. © 2016 IEEE.

2016 3rd International Conference on Electrical Energy Systems, ICEES 2016

Experimental case studies on dead-Time induced oscillation and its mitigation in 5-HP and 10-HP induction motor drives

We report MIS photodetectors fabricated on a SOI substrate in a CMOS-compatible process, exhibiting an enhanced responsivity in the near-infrared (NIR) due to the incorporation of Au-nanoantennas at the optical input port. These nanoantennas modify the propagation of the input optical signals, serving as an effective anti-reflection coating in the NIR wavelength range. The optimal antenna design and the photo-response enhancements have been calculated using detailed FDTD simulations. The maximum responsivity enhancement, 40%, was obtained at 780 nm, while at wavelengths shorter than 720 nm, responsivity is reduced due to absorption losses in the Au-nanoantennas. © 2016 IEEE.

Nanotechnology Materials and Devices Conference, NMDC 2016 - Conference Proceedings

Responsivity enhancement of MIS photodetectors on SOI substrates by plasmonic nanoantennas

A new capacitance-to-digital converter (CDC) that gives a digital output proportional to the measurand kx, independent of its nominal capacitance, is reported in this paper. Various CDCs are available in the market, but their output is a function of the nominal value C0 of the sensor. Thus, a manual correction is required in the output, whenever a new capacitive sensor is interfaced to such CDCs. Moreover, the C0 of the sensors is usually a large value compared with the change in capacitance due to kx. Thus, in a typical CDC, a large percentage of the output counts/bits is used to measure and represent the C0 leading to an underutilization of the hardware as far as the measurement of kx is concerned. The proposed CDC uses a new automatic calibration (AC), employing a switched-capacitor (SC) circuit-based voltage source in a feedback topology, and provides an output independent of the C0 of the sensor employed. The proposed CDC is based on an SC dual-slope technique and possesses the advantages of the dual-slope conversion method. The CDC circuit is designed such that the entire full scale can be used for representing the change in the kx. In addition to this advantage, the AC helps to remove the dependence on the accuracy of the reference capacitor employed in the CDC. A detailed analysis of the effect of various sources of errors in the CDC has been conducted and presented in this paper. A prototype of the proposed CDC has been developed and tested. The results obtained show that the output of the CDC is not a function of the C0 (C0 varied from 60 pF to 1.46 nF) of the sensors interfaced. © 2015 IEEE.

IEEE Transactions on Instrumentation and Measurement

An Easy-to-Interface CDC With an Efficient Automatic Calibration

Automated detection and classification of electrocardiogram (ECG) noise sources can play a crucial role in reliable measurement of ECG parameters for accurate diagnosis of cardiovascular diseases (CVDs) under unsupervised telehealth monitoring and intensive care unit (ICU) applications. Although the methods had quite acceptable detection rates, most methods are too complicated for real-time implementation for wearable cardiac health monitoring devices. Therefore, in this paper, we present a low-complexity algorithm for automatically detecting and classifying the ECG noises including flat line (FL), time-varying noise (TVN), baseline wander (BW), abrupt change (ABC), muscle artifact (MA) and power line interference (PLI). The proposed method is based on the moving average (MAv) and derivative filters and the five temporal features including turning points, global and local amplitude estimates, zerocrossing and autocorrelation peak values. The proposed method is tested and validated using a wide variety of clean and noisy ECG signals taken from the MIT-BIH arrhythmia database and Physionet Challenge database. The method achieves an average sensitivity (Se) of 98.55%, positive productivity (+P) of 95.27% and overall accuracy (OA) of 94.19% for classifying the noises. Results show that the proposed method outperforms the other existing methods. © 2016 IEEE.

2016 International Conference on Signal Processing and Communications, SPCOM 2016

Low-complexity detection and classification of ECG noises for automated ECG analysis system

Automatic modulation classification (AMC) plays an important role in identifying the modulation format of a signal. Most of the existing modulation classifiers assume the signal to be contaminated only by additive white Gaussian noise (AWGN). However, the performances of these traditional classifiers degrade in the presence of non-Gaussian impulsive noise. In this paper, we present a novel automatic modulation classification algorithm based on variational mode decomposition (VMD) in presence of non-Gaussian impulsive noise and additive white Gaussian noise. Our proposed method is a three step process. In the first step, received signal is decomposed into modes. It is clear from simulation results that impulse noise is effectively captured in the first mode. In the second step, all other modes are added except first mode to reduce the impact of impulse noise in the received signal. Then in the third step, cyclostationary feature based classifiers are employed to identify the modulation type. The proposed algorithm is evaluated using well-known existing classifiers for different digital modulation techniques. Comparative results depict the superior performance of our proposed method over other traditional methods under different noise conditions. © 2016 IEEE.

2016 22nd National Conference on Communication, NCC 2016

A novel method for automatic modulation classification under non-Gaussian noise based on variational mode decomposition

In this Letter, the authors propose an efficient and robust method for automatically determining the VT and VF events in the electrocardiogram (ECG) signal. The proposed method consists of: (i) discrete cosine transform (DCT)-based noise suppression; (ii) addition of bipolar sequence of amplitudes with alternating polarity; (iii) zero-crossing rate (ZCR) estimation-based VTVF detection; and (iv) peak-to-peak interval (PPI) feature based VT/VF discrimination. The proposed method is evaluated using 18,000 episodes of different ECG arrhythmias taken from 6 PhysioNet databases. The method achieves an average sensitivity (Se) of 99.61%, specificity (Sp) of 99.96%, and overall accuracy (OA) of 99.92% in detecting VTVF and non-VTVF episodes by using a ZCR feature. Results show that the method achieves a Se of 100%, Sp of 99.70% and OA of 99.85% for discriminating VT from VF episodes using PPI features extracted from the processed signal. The robustness of the method is tested using different kinds of ECG beats and various types of noises including the baseline wanders, powerline interference and muscle artefacts. Results demonstrate that the proposed method with the ZCR, PPI features can achieve significantly better detection rates as compared with the existing methods. © 2016 The Institution of Engineering and Technology.

Healthcare Technology Letters

Efficient and robust ventricular tachycardia and fibrillation detection method for wearable cardiac health monitoring devices

Removal of muscle artifacts from the ECG signals is crucial for a reliable and accurate measurement of local features of ECG signals. In this paper, we present an automatic method for removal of muscle artifacts from ECG signals, based on four steps: decomposing ECG signal using sparse signal decomposition on mixed dictionaries; obtaining QRS complex signal; determining time-instants of R-peak; and removal of muscle artifacts from ECG signal. The noise reduction performance of the proposed method is tested and validated using ECG signals taken from a standard MIT-BIH Arrhythmia database. The reconstructed signals are assessed using both subjective quality assessment test and objective quality assessment metrics. Performance evaluation results show that the proposed method outperforms other existing ECG denoising methods inadequately removing the muscle artifacts without significantly distorting the morphologies of P-wave, QRS-complex and T-wave of the ECG signals. © 2016 IEEE.