Linear convolution using UT Vedic multiplier

Kishore, K. Hari; Noorbasha, Fazal; Sandeep, K. Sai; Bhupesh, D N. V.; Imran, SK Khadar; Sowmya, KR

doi:10.14419/ijet.v7i2.8.10471

Cited by 10 publications

(3 citation statements)

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“…Deep learning concepts for computer vision gave an idea of convolutional neural networks. Its main area of application includes image and video analysis [28]. Flattened image pixels, when used with a feed-forward network, give a bad performance with less accuracy.…”

Section: Convolutional Neural Networkmentioning

confidence: 99%

Data Science and Deep Learning Applications in the E-Commerce Industry: A Survey

Pradeep¹,

M²,

Satyanarayana³

2020

INDJCSE

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The E-Commerce industry is a new way of shopping. Most manufacturers prefer to sell their products on E-commerce websites because of low maintenance and high returns. This paper highlights the application of data science and deep learning methodologies to drive the E-commerce business. The first part of the paper explains the role of data science to identify potential customers, items recommendations and fraud detections. Different stages of building E-commerce websites and the role of proper handling of data is then highlighted. The second part of the paper is about the use of deep learning approaches like Recurrent neural networks in analysing textual information is presented with a demonstration of three architectures. At last, the importance of convolutional neural networks in the E-commerce industry is presented. Fashion related images like dresses, shoes and bags are classified using two separate convolution neural network architectures.

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Section: Convolutional Neural Networkmentioning

confidence: 99%

Data Science and Deep Learning Applications in the E-Commerce Industry: A Survey

Pradeep¹,

M²,

Satyanarayana³

2020

INDJCSE

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“…Therefore, strong multipliers are used to get the square of a binary integer. Some of the request multipliers like Braun, Wallace tower, Dadda multiplier are used in most high-speed applications [9][10][11][12]; Booth multiplier is used in Baugh-Wooley 2's methods [4]. The Vedic multipliers are also evolving into the patterns other than traditional multipliers.…”

Section: Introductionmentioning

confidence: 99%

High speed VLSI Squaring unit of Binary Numbers Design with Yavadunam Sutra and Bit Reduction

Bhavani*,

Lakshmi,

Sai

et al. 2019

IJITEE

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Vedic Mathematics is an ancient Indian algebra in which 16 sutras are used to measure. For excellent performance, most high-speed applications such as cryptography and digital signal processing need powerful and high-speed multipliers. Squaring is a specific case of multiplication. A specialized squaring device can greatly boost the measurement period and significantly reduce the delay. This study discusses the concept of a new square architecture utilizing Vedic-mathematics sutra "Yavadunam." The proposed method uses the amount deficit from the closest base to calculate every operand's circle. The square of a larger number of magnitude is reduced by this method to a smaller multiplication of magnitude and an addition operation

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“…The Han-Carlson adder tolerant fault is described in detail. The Triple Modular Redundancy strategy is introduced to minimize the deterioration of the throughput in the presence of faulty adder [12][13][14][15].Due to its faster running, standard configuration and balanced loading in internal nodes compared to other parallel prefix adders, Han-Carlson adders are popular choice in high speed ALU architecture. Next they address the Han-Carlson adder model, activity that is important from the point of view of fault tolerance [16][17][18][19][20].Han-Carlson adder has a strong fanout trade off, number of logic levels and number of black cells.…”

Section: Introductionmentioning

confidence: 99%

A Fault Tolerant Han-Carlsonadder using Tmr Technique

Rooban¹,

Divya²,

Preethi³

et al. 2019

IJRTE

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A fault tolerant Han-Carlson adder is implemented using TMR technique. This paper suggests a technique of Triple Mode Redundancy (TMR) in which the vote is processedto produce a single output by a majority voting system.Synthesis and simulation are performed using Vivado(Xilinx). The circuitry is basically repeated in triplicate, as the name suggests, with a voting circuit used to transmit to the output the majority rule signals.

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Linear convolution using UT Vedic multiplier

Cited by 10 publications

References 0 publications

Data Science and Deep Learning Applications in the E-Commerce Industry: A Survey

Data Science and Deep Learning Applications in the E-Commerce Industry: A Survey

High speed VLSI Squaring unit of Binary Numbers Design with Yavadunam Sutra and Bit Reduction

A Fault Tolerant Han-Carlsonadder using Tmr Technique

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