Informatics Publishing Limited

Bhavin S. Sedani ¹, Nirali A. Kotak ², Kalpesh H. Wandra ³, G. R. Kulkarni ⁴

Affiliations
1 Department of Electronics & Communication Engineering, VVP Engineering College, Vaidi Virda, Rajkot, Gujarat, IN
2 Department of Electronics & Communication Engineering, C.U. Shah College of Engineering and Technology, Wadhwan, Gujarat, IN
3 Department of Computer Engineering, C.U. Shah College of Engineering and Technology, Wadhwan, Gujarat, IN
4 C.U. Shah College of Engineering and Technology, Wadhwan, Gujarat, OM

Abstract

This paper present the wireless broadband connectivity using WiMAX (Worldwide Interoperability for Microwave Access), earlier technology only provides local wireless connectivity (i.e.Wi-Fi). WiMAX provides an appropriate solution to certain rural access zones that are today prevented from having access to broadband internet because of cost consideration. WiMAX is a second generation protocol that allows for more efficient bandwidth use, interference avoidance, and is intended to allow higher data rates over long distances. Basically by analyzing the structure of WiMAX, it can be observed that it comprises of two layers, Physical layer based on Orthogonal Frequency Division Multiplexing (OFDM) which is a promising technique for broadband wireless communication because it can combat inter-symbol interference caused by the dispersive fading of wireless channel. This paper starts with the introduction to WiMAX, its standards and salient features. In the second phase, the structure of WiMAX system is analyzed and simulated results for OFDM results along with GUI is presented. In the third phase, the comparative analysis between present status of WiMAX and future technological advancement in the present system has been done which includes latest technical aspects such as MIMO, AAS, AMS, Scalable OFDMA structure along with simulation results, etc.

Keywords

Wi-Fi, MAN, WiMAX and OFDM.

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Avani R. Vasant ¹, Sandeep R. Vasant ², G. R. Kulkarni ³

Affiliations
1 Shinghania University, Rajasthan, IN
2 Saurashtra University, Gujarat, IN
3 C.U. Shah College of Engineering Technology, Wadhwan, IN

Abstract

Handwritten Documents are very important part of the day-to-day life. Documents are very important for the communication purpose. With the invention of the Digital Computers and machine learning algorithms the automatic reading of such handwritten documents using Computer has been addressed by many researchers. Such automated Systems enables computers to process handwritten documents faster and efficient. In order to implement a very good recognition system that gives higher recognition rates, we need various pre-processing steps to be applied to the handwritten documents. This paper presents various pre-processing steps to be applied to the offline scanned Gujarati Handwritten Characters.

Keywords

Gujarati Characters, Pre-Processing, Recognition.

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Komal R. Borisagar ¹, Dipesh G. Kamdar ², G. R. Kulkarni ³

Affiliations
1 Department of Electronics & Communication Engineering, Atmiya Institute of Technology and Science, Rajkot, Gujarat, IN
2 Department of Electronics & Communication Engineering, VVP Engineering College, Rajkot, Gujarat, IN
3 C.U. Shsh College of Engineering and Technology, Wadhwan, Gujarat, IN

Abstract

A desired signal corrupted by additive noise can often be recovered by an adaptive noise canceller using the least mean squares (LMS) algorithm. A major disadvantage of the LMS algorithm is its excess mean-squared error, or misadjustment, which increases linearly with the desired signal power. This leads to degrading performance when the desired signal exhibits large power fluctuations and is a serious problem in many speech processing applications. This work considers two modified LMS algorithms, the weighted sum and sum methods, designed to solve this problem by reducing the size of the steps in the weight update equation when the desired signal is strong. The weighted sum method is derived from an optimal method (also developed in this work), which is not generally applicable because it requires quantities unavailable in a practical system. The previously proposed, but ad hoc, sum method is analyzed and compared to the weighted sum method. Analysis of the two modified LMS algorithms indicates that either one provides substantial improvements in the presence of strong desired signals and similar performance in the presence of weak desired signals, relative to the unmodified LMS algorithm. Computer simulations with both uncorrelated Gaussian noise and speech signals confirm the results of the analysis and demonstrate the effectiveness of the modified algorithms. The modified LMS algorithms are particularly short-time power levels.

Keywords

Adaptive Filtering, Adaptive Noise Cancellation, LMS Algorithm, Noise Reduction.

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Tejas P. Patalia ¹, G. R. Kulkarni ²

Affiliations
1 V.V.P. Engineering College, Rajkot, Gujarat, IN
2 C.U. Shah College of Engineering & Technology, Surendranagar, Gujarat, IN

Abstract

The goal of this study of traditional heuristic methods and genetic algorithm is to determine strength of Genetic Algorithm over all traditional heuristic methods. It gives a clear idea of how genetic algorithm works. It gives the idea of various sub methods used in genetic algorithm to improve the results and outcome. Basically genetic algorithm and all traditional heuristic methods are used for optimization. Optimization problems are class NP complete problems. Genetic algorithm can be viewed as an optimization technique which exploits random search within a defined search space to solve a problem by some intelligence ideas of nature.

Keywords

Heuristicmethods, Geneticalgorithm, Chromosomes, Mutation.

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Samaneh Valipour ¹, G. R. Kulkarni ², A. D. Shaligram ²

Affiliations
1 Department of Electronic Science, Pune University, Pune, Maharashtra, IN
2 Department of Physics, Pune University, Pune, Maharashtra, IN

Abstract

A major challenge related to the removal of Ocular Artifacts (OA) from Electroencephalogram (EEG) signals is the lack of a consensus about one superior standard OA removal algorithm among all, due to unavailability of both natural artifactfree EEG signal and a standard performance evaluation criterion. The present paper discusses the various validated performance criteria often used in research papers for considering the efficiency of the OA removal algorithms. These metrics can be measured in the MATLAB software. In addition to natural EEG signals, artificial or simulated signals are also considered in this study. Some of these performance criteria are commonly used for both real and simulated signals, while others are appropriate only for one of them specifically. However, evaluation of a simulated signal can be easier than a real one because of the availability of artifact-free EEG signals in a simulation study, evaluation using a real signal is more trustworthy than simulated one. Hence, for more reliable and precise efficiency considering of an OA removal algorithm, employing both signals, is recommended. Further, because of the non-stationary nature of real EEG signals, the comparison of an algorithm with others, via implementing them on the same signals, will be meaningful and applicable. The present work will help researchers in recording the efficiency of their algorithms, as well as comparing the performance of their methods with others for reaching a consensus in OA removal.

Keywords

EEG, EOG, Ocular Artifact Removal, Performance Metrics

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