Research Cell: An International Journal of Engineering Sciences

Ranjit Kaur ¹, Damanpreet Singh ²

Affiliations
1 Department of Electronics and Communication, Punjabi University, Patiala, IN
2 Department of Computer Science, Sant Longowal Institute of Engineering and Technology, Longowal, IN

Abstract

In this paper band pass (BP) and band stop (BS) infinite impulse response (IIR) filter is designed using particle swarm optimization (PSO) algorithm.The magnitude response of the IIR filter is approximated using L₁-approximation error criterion. The PSO algorithm is a optimization technique inspired by genetics and natural evolution. The method enhances the search capability and provides a fast convergences for calculating the optimal filter coefficients. The filter designed based on L₁-approximation error possesses flat passbands and stopbands while keeping the transition band comparable to that of the least square design. A comparison has been made with other design techniques, demonstrating that PSO with enhanced diversity and convergence gives better or at least comparable results or designing digital IIR filters than the existing genetic algorithm based methods.

Keywords

Digital IIR Filters, Particle Swarm Optimization, L₁-Approximation Error, Magnitude Response, Stability.

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Arvind Kumar ¹, Damanpreet Singh ¹

Affiliations
1 Department of Computer Science and Engineering, Sant Longowal Institute of Engineering and Technology, Longowal, Sangrur, Punjab, IN

Abstract

In the past decades, Wireless Sensor Network (WSN) has become a wide area of research. In WSN, numerous sensor nodes are randomly setup with different energy level. Energy acts as power source and is available to each sensor node in limited quantity. The limiting factor is that sensor nodes are energy constrained and recharging or replacing battery is costly and complex process. This paper explores the different energy consumption factors which effect the lifetime and performance of the WSN's. The main factors which effect the energy consumption in WSN's are scalability, load balancing, reliability, communication, collision, over-hearing, ideal listing and latency. Researchers have proved that the node near to sink node discharge very fastly. Apart from these, most of the energy is consumed during the transfer of data from sender to receiver. In this paper effort is made to analyze the effect of different factors on energy consumption in WSN's.

Keywords

Wireless Sensor Networks, Energy efficiency, Scalability, Load balancing, Reliability, Over-Hearing,Latency.

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Mandeep Kaur ¹, Ranjit Kaur ¹, Damanpreet Singh ²

Affiliations
1 Department of Electronics and Communication Engineering, Punjabi University, Patiala, IN
2 SLIET, Longowal, Punjab, IN

Abstract

Processing of signals requires designing and implementation of systems called Filters. Filter design depend on its type, structure and the method to which it comes in practice. This paper discussed the various realization of Digital Finite-Duration Impulse Response (FIR) filters with its graphical representation. The purpose of using the realization and the graphical representation is to find the critical and shortest path using different algorithm. The realization can be done using FDA tool or coding in MATLAB. The graphical representation way is done in form of Data Flow Graph in term of nodes and edges.

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Sangeet Pal Kaur ¹, Ranjit Kaur ¹, Damanpreet Singh ²

Affiliations
1 Department of Electronics and Communication Engineering, Punjabi University, Patiala, IN
2 SLIET, Longowal, Sangrur, Punjab, IN

Abstract

The electrocardiogram (ECG) is the graphical representation of heart's functionality. It is an important tool used for the diagnosis of cardiac abnormalities. ECG signals are usually weak and susceptible to external noise and interference. Adaptive filter is a good tool to reduce the influence of ambient noise/interference on the ECG signals. Adaptive filter uses Least mean squares (LMS) algorithm, as one of most popular adaptive algorithms for active noise cancellation (ANC). The goal of the paper is to show the comparison based on signal to noise ratio of different adaptive filter algorithms like LMS, Normalized LMS (NLMS), Normalized Signed Regressor LMS (NSRLMS), Recursive Least Squares (RLS), Normalized Sign-Sign LMS (NSSLMS), used for the analysis of ECG signals with noise. The filter needs two input: the signal (primary input) and an impulse correlated with the deterministic component (reference input). Several signals to noise ratio were considered. The adaptive filters essentially minimize the mean-squared error between a primary input, which is the noisy ECG, and a reference input, which is either noise that is correlated in some way with the noise in the primary input or a signal that is correlated only with ECG in the primary input.

Keywords

ECG Signal, Noise, Adaptive Filtering, LMS, NLMS, RLS, NSSLMS.

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Ranjit Kaur ¹, Damanpreet Singh ²

Affiliations
1 Department of Electronics and Communication Engineering, Punjabi University, Patiala, IN
2 Department of CSE, Sant Longowal Institute of Engineering & Technology, Longowal, IN

Abstract

Digital Differentiator (DD) play a very important role to find out and approximate the first, second, or higher-order derivative of a digital signals. In this paper real-coded genetic algorithm (RCGA) is proposed for the design of finite impulse response (FIR) digital differentiator. The intent of this paper is to apply a real-coded genetic algorithm with arithmetic-average-bound-blend (AABBX) crossover and wavelet mutation operator for the design of digital differentiator. The values of the filter coefficients are optimized with RCGA approach to satisfying prescribed specifications. The proposed method is, not only accurate and robust but also optimal in the least-squares sense.

Keywords

Digital Differentiator (DD), Finite Impulse Response (FIR) Filter, Least-Squares Error, Real-Coded Genetic Algorithm (RCGA), McClellan-Parks Algorithm.

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