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Efficient Neural Recording Amplifier for Brain Machine Interface

International journal of current research and review, 2021, Vol.13 (8), p.54-57

2021

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Accuracy evaluation of a trained neural network by energy efficient approximate 4:2 compressor

Computers & electrical engineering, 2021-06, Vol.92, p.107137, Article 107137

2021

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Supervised Machine Learning for Training a Neural Network as 5:2 Compressor

International journal of innovative technology and exploring engineering, 2019-08, Vol.8 (10), p.2079-2084

2019

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A Neural Network trained to perform as an Imprecise 4:2 Compressor using Machine Learning Algorithm

IOP conference series. Materials Science and Engineering, 2021-01, Vol.1042 (1), p.12014

2021

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Machine Learning Based Power Efficient Approximate 4:2 Compressors for Imprecise Multipliers

2019 32nd International Conference on VLSI Design and 2019 18th International Conference on Embedded Systems (VLSID), 2019, p.221-226

2019

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Low-Power. High-Speed Adversarial Attack based 4:2 Compressor as Full Adder for Multipliers in FIR Digital Filters

2019 IEEE Nordic Circuits and Systems Conference (NORCAS): NORCHIP and International Symposium of System-on-Chip (SoC), 2019, p.1-6

2019

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Training Neural Network as Approximate 4:2 Compressor applying Machine Learning Algorithms for Accuracy Comparison

International Journal of Advanced Trends in Computer Science and Engineering, 2019-04, Vol.8 (2), p.211-215

2019

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Performance Metrics of Inexact Multipliers Based on Approximate 5:2 Compressors

2018 International SoC Design Conference (ISOCC), 2018, p.84-85

2018

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High Speed Multiplier using Embedded Approximate 4-2 Compressor for Image Multiplication

2022 First International Conference on Artificial Intelligence Trends and Pattern Recognition (ICAITPR), 2022, p.1-5

2022

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Design and Analysis of a Feed Forward- Binary Neural Network with Adversarial Attack Against Machine Learning Based 4:2 Compressor

SSRN Electronic Journal

MADDISETTI, LAVANYA

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Efficient Neural Recording Amplifier for Brain Machine Interface

Accuracy evaluation of a trained neural network by energy efficient approximate 4:2 compressor

Supervised Machine Learning for Training a Neural Network as 5:2 Compressor

A Neural Network trained to perform as an Imprecise 4:2 Compressor using Machine Learning Algorithm

Machine Learning Based Power Efficient Approximate 4:2 Compressors for Imprecise Multipliers

Low-Power. High-Speed Adversarial Attack based 4:2 Compressor as Full Adder for Multipliers in FIR Digital Filters

Training Neural Network as Approximate 4:2 Compressor applying Machine Learning Algorithms for Accuracy Comparison

Performance Metrics of Inexact Multipliers Based on Approximate 5:2 Compressors

High Speed Multiplier using Embedded Approximate 4-2 Compressor for Image Multiplication

Design and Analysis of a Feed Forward- Binary Neural Network with Adversarial Attack Against Machine Learning Based 4:2 Compressor

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