Implementation of FIR Filters through Inner product Units and Parallel Accumulations

Finite Impulse Response (FIR) filters are pivotal in digital signal processing, finding applications in diverse fields like audio processing, telecommunications, and biomedical signal analysis. This work presents an enhanced implementation methodology for FIR filters utilizing inner product computat...

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Bibliographic Details
Published in:Turkish journal of computer and mathematics education 2024-03, Vol.15 (1), p.212-217
Main Authors: Krishnarao, P.V., Vandana, Dasari, Manasa, Bokkisam Venkata, Pavanim, Dasari, Harshitha, Guntumadugu Pavani
Format: Article
Language:English
Subjects:
Algorithms
Design specifications
Digital signal processing
Efficiency
FIR filters
Fourier transforms
Mathematics education
Neural networks
Number systems
Optimization techniques
Power
Real time
Signal analysis
Signal processing
Sound filters
Wavelet transforms
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Summary:Finite Impulse Response (FIR) filters are pivotal in digital signal processing, finding applications in diverse fields like audio processing, telecommunications, and biomedical signal analysis. This work presents an enhanced implementation methodology for FIR filters utilizing inner product computation and parallel accumulations. In the existing, FIR filters are typically implemented using convolution techniques, basic adders, and multipliers, which involve sequential processing and intensive computational resources. This method often leads to latency issues and limits real-time applications. Moreover, traditional implementations suffer from inefficiencies in utilizing hardware resources optimally, leading to suboptimal performance. The proposed methodology overcomes these limitations by leveraging inner product computations and parallel accumulation techniques. By exploiting inherent parallelism in the filtering process, the proposed method significantly reduces latency and enhances throughput.
ISSN:1309-4653
1309-4653
DOI:10.61841/turcomat.v15i1.14614