Design of an Area-Efficient FinFET-Based Approximate Multiplier in 32-nm Technology for Low-Power Application

Kumar, Vivek; Selvaraj, Ratnam J.

doi:10.1007/978-981-13-3393-4_52

Cited by 8 publications

(2 citation statements)

References 14 publications

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“…The convolution based architecture are advantages in easy implementation but more number of elements especially multipliers while the lifting based scheme reduces the multiplier and pipelining stages Wei Zhang et al (2012), Mohanty et al(2011) . Several architectures using different multipliers are presented in literature (Senthilkumar, 2019(Senthilkumar, , 2018 most architecture needs memory to save intermediate results. Some architectures for 2D transform used multilevel analysis using scalable structures (Yusong and Ching, 2013), folded architecture and digital serial architecture (Keshab and shri 2009).…”

Section: Literature Surveymentioning

confidence: 99%

An Efficient Discrete Wavelet Transform Architecture with Low Power and Multiplier-Less Structure for Pervasive Biomedical Image Processing Application

Guptha¹,

Rao²,

Selvaraj³

2023

EAI Endorsed Trans Perv Health Tech

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INTRODUCTION: Over the past several years analysis of image has moved from larger system to pervasive portable devices. For example, in pervasive biomedical systems like PACS-Picture achieving and Communication system, computing is the main element. Image processing application for biomedical diagnosis needs efficient and fast algorithms and architecture for their functionality. Future pervasive systems designed for biomedical application should provide computational efficiency and portability. The discrete wavelet transform (DWT) designed in on-chip been used in several applications like data, audio signal processing and machine learning.OBJECTIVES: The conventional convolution based scheme is easy to implement but occupies more memory , power and delay. The conventional lifting based architecture has multiplier blocks which increase the critical delay. Designing the wavelet transform without multiplier is a effective task especially for the 2-D image analysis. Without multiplier Daubechies wavelet implementation in forward and inverse transforms may find efficient. The objective of the work is on obtaining low power and less delay architecture.METHODS: The proposed lifting scheme for two dimensional architecture reduces critical path through multiplier less and provides low power, area and high throughput. The proposed multiplier is delay efficient.RESULTS: The architecture is Multiplier less in the predict and update stage and the implementation carried out in FPGA by the use of Quartus II 9.1 and it is found that there is reduction in consumption of power at approximately 56%. There is reduction in delay due to multiplier less architecture.CONCLUSION: multiplier less architecture provides less delay and low power. The power observed is in milliwatts and suitable for high speed application due to low critical path delay.

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Section: Literature Surveymentioning

confidence: 99%

An Efficient Discrete Wavelet Transform Architecture with Low Power and Multiplier-Less Structure for Pervasive Biomedical Image Processing Application

Guptha¹,

Rao²,

Selvaraj³

2023

EAI Endorsed Trans Perv Health Tech

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“…The feature extraction methods using the linear discriminant analysis (LDA) provides higher recognition rates but, the hardware utilization should be optimized and simulated [6]. Amplifiers are required to increase the strength of biomedical signal, which is designed by op-amps recommended by FPGA kit [18,19].…”

Section: Introductionmentioning

confidence: 99%

Hybrid statistical and recurrent neural network architecture implementation in FPGA device used for severe acute respiratory syndrome coronavirus detector

Senthilkumar¹,

Thenmozhi²,

Kumudavalli³

et al. 2023

IFS

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The Severe Acute Respiratory Syndrome (SARS) are caused by the strain of the corona virus causes cold and influenza. In recent years, the covid pandemic spread throughout the world killing millions of people. The fatality rate has increased and it also leads to pneumonia for breathing problems. Several methods like wavelet filter banks, time series methods, Neural networks was developed for the diagnosis of severe acute respiratory syndrome coronavirus, still the accuracy can be improved. Less works is carried out for hardware implementation for syndrome detectors. This proposed work represents the FPGA (Field Programmable Gate Array) implementation of the hybrid method using Convolutional Recurrent neural network and Independent Components Analysis (ICA). The architecture extracts the ccomplex features from ECG (Electrocardiogram) samples. The hybrid Statistical and Recurrent Neural Network (RNN) Architecture implementation in a real time hardware detects the Severe Acute Respiratory Syndrome presented. The proposed method can be implemented in MATLAB, Embedded and DSP (Digital Signal Processor). But, the FPGAs consume less power computationally efficient. Since, ICA is an efficient method due to its blind source separation property accumulate the extraction of features accurate described. The mathematical model for the analysis of ECG signal using RNN is analyzed and based on that the proposed model is selected. On investigation the hybrid method using the statistical and neural network model is efficient in the analysis of biomedical signal especially ECG. The proposed ICA based RNN model is mathematically evaluated and tested with real time data. For implementation, Quartus software is used for effectiveness of the proposed model.

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High Speed, Low Matchline Voltage Swing and Search Line Activity TCAM Cell Array Design in 14 nm FinFET Technology

Prasanth¹,

Ramireddy²,

priya³

et al. 2019

Lecture Notes in Electrical Engineering

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Design of an Area-Efficient FinFET-Based Approximate Multiplier in 32-nm Technology for Low-Power Application

Cited by 8 publications

References 14 publications

An Efficient Discrete Wavelet Transform Architecture with Low Power and Multiplier-Less Structure for Pervasive Biomedical Image Processing Application

An Efficient Discrete Wavelet Transform Architecture with Low Power and Multiplier-Less Structure for Pervasive Biomedical Image Processing Application

Hybrid statistical and recurrent neural network architecture implementation in FPGA device used for severe acute respiratory syndrome coronavirus detector

High Speed, Low Matchline Voltage Swing and Search Line Activity TCAM Cell Array Design in 14 nm FinFET Technology

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