Purpose

This paper aims to concentrate on an efficient finite impulse response (FIR) filter architecture in combination with the differential evolution ant colony algorithm (DE-ACO). For the design of FIR filter, the evolutionary algorithm (EA) is found to be very efficient because of its non-conventional, nonlinear, multi-modal and non-differentiable nature. While focusing with frequency domain specifications, most of the EA techniques described with the existing systems diverge from the power related matters.

Design/methodology/approach

The FIR filters are extensively used for many low power, low complexities, less area and high speed digital signal processing applications. In the existing systems, various FIR filters have been proposed to focus on the above criterion.

Findings

In the proposed method, a novel DE-ACO is used to design the FIR filter. It focuses on satisfying the economic power utilization and also the specifications in the frequency domain.

Originality/value

The proposed DE-ACO gives outstanding performance with a strong ability to find optimal solution, and it has got quick convergence speed. The proposed method also uses the Software integrated synthesis environment (ISE) project navigator (p.28xd) for the simulation of FIR filter based on DE-ACO techniques.

中文翻译：

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使用改进的差分进化蚁群优化算法进行 FIR 滤波器设计的高效 VLSI 架构

目的

本文旨在集中于结合差分进化蚁群算法 (DE-ACO) 的高效有限脉冲响应 (FIR) 滤波器架构。对于FIR滤波器的设计，进化算法（EA）因其非传统、非线性、多模态和不可微分的特性而被发现是非常有效的。在关注频域规范的同时，现有系统中描述的大多数 EA 技术都与功率相关问题有所不同。

设计/方法/方法

FIR 滤波器广泛用于许多低功耗、低复杂性、较小面积和高速数字信号处理应用。在现有系统中，已经提出了各种FIR滤波器来关注上述标准。

发现

在所提出的方法中，一种新颖的 DE-ACO 用于设计 FIR 滤波器。它侧重于满足经济用电和频域规格。

原创性/价值

提出的 DE-ACO 具有出色的性能，具有很强的寻找最优解的能力，并且具有较快的收敛速度。所提出的方法还使用软件集成综合环境 (ISE) 项目导航器 (p.28xd) 来模拟基于 DE-ACO 技术的 FIR 滤波器。