In this work, a new class of stochastic gradient algorithm is developed based on q-calculus. Unlike the existing q-LMS algorithm, the proposed approach fully utilizes the concept of q-calculus by incorporating time-varying q parameter. The proposed enhanced q-LMS (Eq-LMS) algorithm utilizes a novel, parameterless concept of error-correlation energy and normalization of signal to ensure high con...

Our society where communication through modern technology is prominent, seeking high speed voice, video and data in quantities that could not be imagined even a decade ago. The mobility and channel impairments have added more challenges. Multi Carrier Code Division Multiple Access (MC-CDMA) system is an attractive choice for high speed wireless communication as it avoids the problem of Inter Sy...

This paper proposes wavelet packets for use in ultra wideband communications. The pulse shapes that are generated are quasi orthogonal and have almost identical time duration. After normalization, an M-ary signaling set can be constructed allowing higher data rate. Finally, the performance of such a system when multipath propagation occurs is investigated by computer simulations. In order to co...

In this paper a module consisting of a Fast Least Mean Square (FLMS) filter is modeled and verified to eliminate acoustic echo, which is a problem for hands free communication. However the acoustic echo cancellation (AEC) is modeled using digital signal processing technique especially Simulink Blocksets. The needed algorithm code is generated in Matlab Simulink programming. At the simulation le...

In this paper, event related potential (ERP) generated due to hand movement is detected through the adaptive noise canceller (ANC) from the electroencephalogram (EEG) signals. ANCs are implemented with least mean square (LMS), normalized least mean square (NLMS), recursive least square (RLS) and evolutionary algorithms like particle swarm optimization (PSO), bacteria foraging optimization (BFO)...

In this paper Adaptive filter is designed and simulated using different algorithms for noise reduction in different signals. The developed filter has been analyzed using Least Mean Square (LMS), Normalized Least Mean Square (NLMS) and Recursive Least Squares (RLS) algorithms for sinusoidal, chirp and saw-tooth signals. The performance of developed filter has been compared interms of Rate of Con...

Adaptive filter is an efficient method to filter ECG signal, because it does not need the signal statistical characteristics. In this paper we present a Gaussian & novel adaptive filter for removing the Baseline wander & power line interference from ECG signals based on recursive least mean square (RLMS) algorithm & Normalized least mean square (NLMS) algorithm. These algorithms are derived bas...

This study presents a data-driven approach in conjunction with an adaptive extended Kalman filter (AEKF) to estimate lithium-ion batteries' state of charge (SOC) online. The Thevenin battery model is used evaluate the effects using voltage and current. advantages Lagrange multiplier method are utilized battery. continuously decreases error adjust gain AEKF for accurate SOC estimation. Various c...

This paper explores the potential of several popular equalization techniques and proposes new approaches to overcome their disadvantages. Such as the conventional least-mean-square (LMS ) algorithm, the recursive least-squares ( RLS ) algorithm, the filtered-X LMS algorithm and their development. An H 2 optimal initialization has been proposed to overcome the slow convergence problem while keep...