Design of Higher Order Matched FIR Filter Using Odd and Even Phase Process

IF 2 4区 计算机科学 Q2 Computer Science
V. Magesh, N. Duraipandian
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引用次数: 1

Abstract

The current research paper discusses the implementation of higher order-matched filter design using odd and even phase processes for efficient area and time delay reduction. Matched filters are widely used tools in the recognition of specified task. When higher order taps are implemented upon the transposed form of matched filters, it can enhance the image recognition application and its performance in terms of identification and accuracy. The proposed method i.e., odd and even phases’ process of FIR filter can reduce the number of multipliers and adders, used in existing system. The main advantage of using higher order tap-matched filter is that it can reduce the area required, owing to its odd and even processes. Further, it also successfully reduces the time delay, especially in case of high order demands. The performance of higher order matched filter design, using odd and even phase process, was analyzed using Xilinx 9.1 ISE Simulator. The study results accomplished reduction in area, 70% increase in throughput compared to traditional implementation and reduced time delay. In addition to these, Vedic multiplier-based FIR is modified with a tree-based MAM that reduces the number of shifter and adder to replace the multiplier.
基于奇偶相位处理的高阶匹配FIR滤波器设计
本文讨论了利用奇偶相位过程实现高阶匹配滤波器设计,以有效地减少面积和时间延迟。匹配滤波器是一种广泛应用于特定任务识别的工具。在匹配滤波器的转置形式上实现高阶抽头,可以提高图像识别的应用和识别精度。本文提出的FIR滤波器奇偶相位处理方法可以减少现有系统中使用的乘法器和加法器的数量。使用高阶分接匹配滤波器的主要优点是,由于其奇偶过程,它可以减少所需的面积。此外,它还成功地减少了时间延迟,特别是在高订单需求的情况下。利用Xilinx 9.1 ISE模拟器对奇偶相位高阶匹配滤波器设计的性能进行了分析。研究结果表明,与传统实现相比,该方法减少了面积,提高了70%的吞吐量,减少了时间延迟。除此之外,基于吠陀乘数的FIR被修改为基于树的MAM,减少了移位器和加法器的数量,以取代乘数。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Intelligent Automation and Soft Computing
Intelligent Automation and Soft Computing 工程技术-计算机:人工智能
CiteScore
3.50
自引率
10.00%
发文量
429
审稿时长
10.8 months
期刊介绍: An International Journal seeks to provide a common forum for the dissemination of accurate results about the world of intelligent automation, artificial intelligence, computer science, control, intelligent data science, modeling and systems engineering. It is intended that the articles published in the journal will encompass both the short and the long term effects of soft computing and other related fields such as robotics, control, computer, vision, speech recognition, pattern recognition, data mining, big data, data analytics, machine intelligence, cyber security and deep learning. It further hopes it will address the existing and emerging relationships between automation, systems engineering, system of systems engineering and soft computing. The journal will publish original and survey papers on artificial intelligence, intelligent automation and computer engineering with an emphasis on current and potential applications of soft computing. It will have a broad interest in all engineering disciplines, computer science, and related technological fields such as medicine, biology operations research, technology management, agriculture and information technology.
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