Indian Institute of Technology Bhubaneswar

About: Indian Institute of Technology Bhubaneswar is a education organization based out in Bhubaneswar, India. It is known for research contribution in the topics: Large Hadron Collider & Computer science. The organization has 1185 authors who have published 3132 publications receiving 48832 citations.

Error Saturation Nonlinearities for Robust Incremental LMS over Wireless Sensor Networks

Abstract: The data collected by sensor nodes over a geographical region is contaminated with Gaussian and impulsive noise. The conventional gradient-based distributed adaptive estimation algorithms exhibit good performance in the presence of Gaussian noise but perform poorly in impulsive noise environments. Therefore, the objective of this article is to propose a robust distributed adaptive algorithm that alleviates the effect of impulsive noise. An error saturation nonlinearity-based robust distributed strategy is proposed in an incremental cooperative network to estimate the desired parameters in impulsive noise. The steady-state analysis of the proposed error saturation nonlinearity incremental least mean squares (SNILMS) algorithm is carried out by employing the spatial-temporal energy conservation principle. Both theoretical and simulation results show that the presence of the error nonlinearity has made the proposed SNILMS algorithm robust to impulsive noise.

Intelligent optimization of renewable resource mixes incorporating the effect of fuel risk, fuel cost and CO2 emission

Abstract: Power system planning is a capital intensive investment-decision problem. The majority of the conventional planning conducted since the last half a century has been based on the least cost approach, keeping in view the optimization of cost and reliability of power supply. Recently, renewable energy sources have found a niche in power system planning owing to concerns arising from fast depletion of fossil fuels, fuel price volatility as well as global climatic changes. Thus, power system planning is under-going a paradigm shift to incorporate such recent technologies. This paper assesses the impact of renewable sources using the portfolio theory to incorporate the effects of fuel price volatility as well as CO2 emissions. An optimization framework using a robust multi-objective evolutionary algorithm, namely NSGA-II, is developed to obtain Pareto optimal solutions. The performance of the proposed approach is assessed and illustrated using the Indian power system considering real-time design practices. The case study for Indian power system validates the efficacy of the proposed methodology as developing countries are also increasing the investment in green energy to increase awareness about clean energy technologies.

Herman rings of meromorphic maps with an omitted value

Abstract: We investigate the existence and distribution of Herman rings of transcendental meromorphic functions which have at least one omitted value. If all the poles of such a function are multiple then it has no Herman ring. Herman rings of period one or two do not exist. Functions with a single pole or with at least two poles one of which is an omitted value have no Herman ring. Every doubly connected periodic Fatou component is a Herman ring.

De-Correlated Improved Adaptive Exponential FLAF-Based Nonlinear Adaptive Feedback Cancellation for Hearing Aids

Abstract: Modern-day digital hearing aids are prone to an unavoidable acoustic feedback phenomenon, degrading sound quality and speech intelligibility. The linear adaptive feedback cancellation (AFC) systems based on finite-impulse-response filters do not yield satisfactory performance under nonlinearity encountered in the feedback path. In an endeavor to overcome this, a de-correlated improved adaptive exponential functional link adaptive filter (DI-AEF)-based nonlinear AFC (NAFC) system is developed in this paper. It utilizes cross terms of the input samples and trigonometrical expansion with exponentially varying amplitude. To save computations, the delayed outputs of the feedback canceler are appended at the input layer, inspired by the IIR filtering technique. The adaptive de-correlation filter is updated by variable convergence and forgetting factor windowed recursive least square algorithm to address the biased estimation problem. The corresponding update rules, convergence, and bounded-input bounded-output stability conditions have been derived. Extensive simulation results demonstrate the efficacy of the proposed NAFC system for real input signals in terms of perceptual evaluation of speech and audio quality and added stable gain (ASG). The DI-AEF-based system achieves nearly 4-dB improvement in ASG while consuming 53% and 37% less multiplications and additions than the existing nonlinear methods.