Design and Implementation of High Speed II Rand FIR Filter using Pipelining

Along with the advancement in VLSI (Very Large Scale Integration) technology, the implementation of Finite impulse response (FIR) filters and Infinite impulse response (IIR) filters with enhanced speed has become more demanding. This paper aims at designing and implementing a combined pipelining and parallel processing architecture for FIR and IIR filter using VHDL (Very High Speed Integrated Circuit Hardware Descriptive Language) to reduce the power consumption and delay of the filter. The proposed architecture is compared with the original FIR and IIR filter respectively in terms of speed, area, and power. Also, the proposed architecture is compared with existing architectures in terms of delay. The implementation is done by using VHDL codes. FIR and IIR filters structures are implemented at 1200 KHz clock frequency. Synthesis and simulation have been accomplished on Artix-7 series FPGA, target device (xc7a200tfbg676) (speed grade-1) using VIVADO 2016.3.

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“…Where x(n) is the input signal, y(n) is the output signal, bi is the filter coefficients and N is the filter order [5].…”

Section: Fir Filtermentioning

confidence: 99%

Design And Implementation of Combined Pipelining and Parallel Processing Architecture for FIR and IIR Filters Using VHDL

Potsangbam¹,

Kumar

2019

VLSICS

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“…Many studies are presented an optimisations design approach such as dispersed look ahead [13,14], clustered look ahead [14,15] and distributed look ahead [16,17]. All these methods increased the operating frequency using superfluous poles allowing pipelining [18,19]. Though, towards limitation on scale factors and noise effect, these design approaches need intensive computational time the adequate set for zeros and poles and proper order for the sub-filters.…”

Section: Introductionmentioning

confidence: 99%

“…This computation work is required in advance to realise the actual filter. On the other hand, some research works based on optimal design is offered to minimize the consumed computational time, however, the attempt still limited [13][14][15][16][17][18][19][20].…”

Section: Introductionmentioning

confidence: 99%

Optimised Design and Implementation of Band-Pass Filter for Neural Recording System

Al-shueli*

2020

IJRTE

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In this paper, an eight order efficient digital infinite impulse response filter is designed to improve the signal to noise ratio (SNR) and minimise the hardware and power consumption. For this task, an optimisation method has been adapted to reduce the root mean square error and hardware usage. The filter has been designed and analysed using Matlab and Modelsim, the implementation has been synthesis on Xilinx Spartan 3E-100 (xc3s100e) field-programmable gate array board. Moreover, an optimisation process using parallel algorithm has bee adapted for further reduction in the hardware area and power consumption. -Iraq, 1976) is an assist prof. in electronics engineering at University of Thi-Qar/Iraq. His B.Sc. degree in electrical engineering and his M.Sc. degree in electronic and communication engineering were granted from University of Mustansiriyah, Baghdad, Iraq in 1998 and 2000 respectively. Later he was awarded his PhD degree in electronic and electrical engineering from University of Bath, Bath, UK, in 2013. His research interests are electrical resistivity, digital filter design, microelectronic design, digital signal processing. Dr. Al-shueli is a member in IEEE organization, Iraq Section, as well as a member in the Iraqi Engineering Union. The results show the Band Pass Filter effectively functions in real time recording application with significant improvement in the SNR which could achieve high-velocity selective resolution. The present work offers a structure of implementing a band-pass filter on FPGAs using a nonlinear digital filter shows a significant saving of 25.4% in power consumption and 29.9% of the hardware size comparing with the latest algorithm of IIR filter design. Consequently, this is an essential development to enhance the neural signals to be adopted as reference or control signals in artificial limbs devices.

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“…The implementation of FIR and IIR filters on FPGA is carried out in [44] and results showed that pipelined filters shows advantages over non pipelined filters in terms of speed and area on FPGA.…”

Section: Literature Reviewmentioning

confidence: 99%

Vedic Mathematics for Digital Signal Processing Operations: A Review

Gaikwad¹,

Chavan²

2015

IJCA

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Speed improvement in Digital signal processing is considered to be challenging. High speed multipliers and adders are prime requirement for digital filters and for FFT operations.Vedic mathematics is an ancient scheme based on 16 formulas (sutras). These are simple and easy methods which can be directly applied for DSP computations. Many researchers have worked on multiplier designs using Vedic operators. Present paper deals with exhaustive review of literature based on Vedic mathematics. It shows that Vedic mathematics can be used for fast signal processing. Multipliers based on Vedic mathematics can be used for speed improvement, reduction in power consumption, complexity, area etc. Vedic mathematical algorithms can be proved efficient over traditional (existing) methods in FIR and IIR filters for providing effective results in de-noising of biomedical Signal.

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Design and Implementation of High Speed II Rand FIR Filter using Pipelining

Cited by 15 publications

References 7 publications

Design And Implementation of Combined Pipelining and Parallel Processing Architecture for FIR and IIR Filters Using VHDL

Design And Implementation of Combined Pipelining and Parallel Processing Architecture for FIR and IIR Filters Using VHDL

Optimised Design and Implementation of Band-Pass Filter for Neural Recording System

Vedic Mathematics for Digital Signal Processing Operations: A Review

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