A Comparative Study on FIR Filters for Reconfigurable Applications
Moorthi Kiruban,
Raja Jayamani
Issue:
Volume 3, Issue 1, March 2018
Pages:
1-10
Received:
8 May 2017
Accepted:
22 November 2017
Published:
19 January 2018
Abstract: Reconfigurability and low complexity are the two key requirements for finite impulse response (FIR) filters employed in multi standard wireless communication systems. In this article, a comparative study of various adaptive filter architectures, which includes BCSE architecture, constant shift method, programmable shift method, multiple constant method, DA based method are presented. This paper aims at study on efficient adaptive filter architecture in terms of area, EPS (energy per sample) and power. By comparing various methods it is observed that MCM structure involves significantly less area delay product and less energy per sample than the existing block implementation methods of direct- form structure for medium or large filter lengths. The MCM structure involves 14% less ADP and 13% less EPS than that of the existing direct- form block FIR structure.
Abstract: Reconfigurability and low complexity are the two key requirements for finite impulse response (FIR) filters employed in multi standard wireless communication systems. In this article, a comparative study of various adaptive filter architectures, which includes BCSE architecture, constant shift method, programmable shift method, multiple constant me...
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Bridging Communication Gap Among People with Hearing Impairment: An Application of Image Processing and Artificial Neural Network
Ogunsanwo Gbenga Oyewole,
Goga Nicholas,
Awodele Oludele,
Okolie Samuel
Issue:
Volume 3, Issue 1, March 2018
Pages:
11-18
Received:
21 February 2018
Accepted:
8 March 2018
Published:
30 March 2018
Abstract: Before the present study, no sign language recognition system for the Nigeria indigenous sign language particularly Yoruba language has been developed. As a result, this research endeavors at introducing a Yoruba Sign Language recognition system using image processing and Artificial Neural Network (ANN).The proposed system (YSLRS) was implemented and tested. 600 images from 60 different signers were gathered. The images were acquired using vision based method, the different signers were asked to stand in front of a laptop’s camera make sign number from one to ten with their fingers in three different times and the images were stored in a folder. The image dataset was pre-processed for proper presentation for de-noising, segmentation and feature extraction. Thereafter, pattern recognition was done using feed forward back propagation ANN. The study revealed that Median filter with higher PSNR of 47.7 a lower MSE of 1.11, performed better than the Gaussian filter. Furthermore, the efficiency of the developed system was determined using mean square error and the best validation performance occurred at 25 epochs with a MSE of 0.004052, implying than ANN was able to adequately recognize the pattern of the Yoruba signs. Histogram was also used to determine the efficiency of the system, it can be seen that the histogram of the trained, tested and validated error bars were close to zero error, implying that the ANN and Receiver Operating Characteristic (ROC) was used to evaluate the performance of ANN in matching the features of the Yoruba Signs, which shows that ANN performed efficiently, having a high true positive rate and a minimum false positive rate. Finally, YSLRS developed in the study would reduce negative attitudes of victimizations suffered by the hearing-impaired individuals, by bridging communication gap among Nigerian PWD with hearing impairment.
Abstract: Before the present study, no sign language recognition system for the Nigeria indigenous sign language particularly Yoruba language has been developed. As a result, this research endeavors at introducing a Yoruba Sign Language recognition system using image processing and Artificial Neural Network (ANN).The proposed system (YSLRS) was implemented a...
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