FPGA Implementation of a PC-AT Computer to Neural Network Interface

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ISBN 13 :
Total Pages : 104 pages
Book Rating : 4.:/5 (416 download)

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Book Synopsis FPGA Implementation of a PC-AT Computer to Neural Network Interface by : Jeffrey Richard Lewis

Download or read book FPGA Implementation of a PC-AT Computer to Neural Network Interface written by Jeffrey Richard Lewis and published by . This book was released on 1997 with total page 104 pages. Available in PDF, EPUB and Kindle. Book excerpt:

FPGA Implementations of Neural Networks

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Publisher : Springer Science & Business Media
ISBN 13 : 0387284877
Total Pages : 365 pages
Book Rating : 4.3/5 (872 download)

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Book Synopsis FPGA Implementations of Neural Networks by : Amos R. Omondi

Download or read book FPGA Implementations of Neural Networks written by Amos R. Omondi and published by Springer Science & Business Media. This book was released on 2006-10-04 with total page 365 pages. Available in PDF, EPUB and Kindle. Book excerpt: During the 1980s and early 1990s there was signi?cant work in the design and implementation of hardware neurocomputers. Nevertheless, most of these efforts may be judged to have been unsuccessful: at no time have have ha- ware neurocomputers been in wide use. This lack of success may be largely attributed to the fact that earlier work was almost entirely aimed at developing custom neurocomputers, based on ASIC technology, but for such niche - eas this technology was never suf?ciently developed or competitive enough to justify large-scale adoption. On the other hand, gate-arrays of the period m- tioned were never large enough nor fast enough for serious arti?cial-neur- network (ANN) applications. But technology has now improved: the capacity and performance of current FPGAs are such that they present a much more realistic alternative. Consequently neurocomputers based on FPGAs are now a much more practical proposition than they have been in the past. This book summarizes some work towards this goal and consists of 12 papers that were selected, after review, from a number of submissions. The book is nominally divided into three parts: Chapters 1 through 4 deal with foundational issues; Chapters 5 through 11 deal with a variety of implementations; and Chapter 12 looks at the lessons learned from a large-scale project and also reconsiders design issues in light of current and future technology.

Application of FPGA to Real‐Time Machine Learning

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Publisher : Springer
ISBN 13 : 3319910531
Total Pages : 187 pages
Book Rating : 4.3/5 (199 download)

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Book Synopsis Application of FPGA to Real‐Time Machine Learning by : Piotr Antonik

Download or read book Application of FPGA to Real‐Time Machine Learning written by Piotr Antonik and published by Springer. This book was released on 2018-05-18 with total page 187 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book lies at the interface of machine learning – a subfield of computer science that develops algorithms for challenging tasks such as shape or image recognition, where traditional algorithms fail – and photonics – the physical science of light, which underlies many of the optical communications technologies used in our information society. It provides a thorough introduction to reservoir computing and field-programmable gate arrays (FPGAs). Recently, photonic implementations of reservoir computing (a machine learning algorithm based on artificial neural networks) have made a breakthrough in optical computing possible. In this book, the author pushes the performance of these systems significantly beyond what was achieved before. By interfacing a photonic reservoir computer with a high-speed electronic device (an FPGA), the author successfully interacts with the reservoir computer in real time, allowing him to considerably expand its capabilities and range of possible applications. Furthermore, the author draws on his expertise in machine learning and FPGA programming to make progress on a very different problem, namely the real-time image analysis of optical coherence tomography for atherosclerotic arteries.

Exploring FPGA Implementation for Binarized Neural Network Inference

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ISBN 13 :
Total Pages : 41 pages
Book Rating : 4.:/5 (18 download)

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Book Synopsis Exploring FPGA Implementation for Binarized Neural Network Inference by : Li Yang

Download or read book Exploring FPGA Implementation for Binarized Neural Network Inference written by Li Yang and published by . This book was released on 2018 with total page 41 pages. Available in PDF, EPUB and Kindle. Book excerpt: This thesis proposes to implement a new parallel convolutional binarized neural network (i.e. PC-BNN) on FPGA with accurate inference. The embedded PC-BNN is designed for image classification on CIFAR-10 dataset and explores the hardware architecture and optimization of customized CNN topology.

Fpga Implementation of Hopfield Neural Network

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Publisher : LAP Lambert Academic Publishing
ISBN 13 : 9783848435456
Total Pages : 76 pages
Book Rating : 4.4/5 (354 download)

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Book Synopsis Fpga Implementation of Hopfield Neural Network by : Avvaru Srinivasulu

Download or read book Fpga Implementation of Hopfield Neural Network written by Avvaru Srinivasulu and published by LAP Lambert Academic Publishing. This book was released on 2012-03 with total page 76 pages. Available in PDF, EPUB and Kindle. Book excerpt: This work was to establish whether it was possible to achieve a reasonable speedup by implementing FPGA based Hopfield neural networks for some simple constraint satisfaction problems. The results are significant - our initial implementation using standard Xilinx FPGAs yielded 2-3 orders of magnitude speedup over the Sun Blade 2000 workstation comes with 1.2-GHz version of the 64-bit UltraSPARC III Cu processor. The main problem with the work to date is that the problems are both unrealistically small and simplistic. That is the constraints on the N-Queen problem are simpler than those found in many real world scheduling applications. Thus, it is not clear whether we will be able to optimize the neuron structure for more complex problems since the weights matrix may not contain as many zero elements. Thus a new method for speed improvement of Hopfield neural networks for solving constraint satisfaction problems using Field Programmable Gate Arrays (FPGAs) was proposed and implemented.

FGPA Implementation of Artificial Neural Networks for Brain Computer Interface Applications

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Publisher :
ISBN 13 :
Total Pages : 59 pages
Book Rating : 4.:/5 (976 download)

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Book Synopsis FGPA Implementation of Artificial Neural Networks for Brain Computer Interface Applications by :

Download or read book FGPA Implementation of Artificial Neural Networks for Brain Computer Interface Applications written by and published by . This book was released on 2016 with total page 59 pages. Available in PDF, EPUB and Kindle. Book excerpt: Brain-computer interface (BCI) has been extensively studied as a means of restoring sensorimotor functions. The BCI enables individuals to use the electrical activity signals of their own brain that are recorded by electrodes, to control an external device through decoding, translating, and actuating. Most state-of-the-art decoding techniques rely on offline analysis, making it impractical for portable BCI to implement complex computation on hardware. On the other hand, classification capability based on look-up table is limited in onchip implementation. An on-chip intelligent system based on Artificial Neural Network (ANN) has been designed that can effectively perform ECoG data signal decoding of a single finger movement. The main building blocks of this decoding architecture are a hardware friendly version of principle component analysis (PCA) and a multi-layer perceptron (MLP). In this thesis, we mainly focus on the hardware implementation of multi-layer perceptron that can perform movement classification. Training of the neural network is carried out and learned weights are used to model the ANN in Verilog hardware description language and made it FPGA implementable. Various architectures of ANN were considered to optimize the design in terms of performance trade-offs such as area, power, speed and accuracy. Our proposed architecture can predict single finger movements with more than 80% accuracy. This implementation will serve as a pathway to develop a real-time BCI system capable of predicting volitional movement intentions.

Implementation of FPGA-based Artificial Neural Network for Character Recognition

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Publisher :
ISBN 13 :
Total Pages : 104 pages
Book Rating : 4.:/5 (11 download)

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Book Synopsis Implementation of FPGA-based Artificial Neural Network for Character Recognition by : Omar Sadeq Salman

Download or read book Implementation of FPGA-based Artificial Neural Network for Character Recognition written by Omar Sadeq Salman and published by . This book was released on 2014 with total page 104 pages. Available in PDF, EPUB and Kindle. Book excerpt: This project may be seen as a place to begin for learning Artificial Neural Network (ANN).

FPGA Implementation of Reduced Precision Convolutional Neural Networks

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ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (19 download)

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Book Synopsis FPGA Implementation of Reduced Precision Convolutional Neural Networks by : Muhammad Mohid Nabil

Download or read book FPGA Implementation of Reduced Precision Convolutional Neural Networks written by Muhammad Mohid Nabil and published by . This book was released on 2018 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: With the improvement in processing systems, machine learning applications are finding widespread use in almost all sectors of technology. Image recognition is one application of machine learning which has become widely popular with various architectures and systems aimed at improving recognition performance. With classification accuracy now approaching saturation point, many researchers are now focusing on resource and energy efficiency. With the increased demand for learning applications in embedded devices, it is of paramount importance to optimize power and energy consumption to increase utility in these low power embedded systems. In recent months, reduced precision neural networks have caught the attention of some researchers. Reduced data width deep nets offer the potential of saving valuable resources on hardware platforms. In turn, these hardware platforms such as Field Programmable Gate Arrays (FPGAs) offer the potential of a low power system with massive parallelism increasing throughput and performance. In this research, we explore the implementations of a deep learning architecture on FPGA in the presence of resource and energy constraints. We study reduced precision neural networks and implement one such architecture as a proof of concept. We focus on binarized convolutional neural network and its implementation on FPGAs. Binarized convolutional nets have displayed a classification accuracy of up to 88% with some smaller image sets such as CIFAR-10. This number is on the rise with some of the new architectures. We study the tradeoff between architecture depth and its impact on accuracy to get a better understanding of the convolutional layers and their impact on the overall performance. This is done from a hardware perspective giving us better insight enabling better resource allocation on FPGA fabric. Zynq ZCU-102 has been used for accelerator implementation. High level synthesis tool (Vivado HLS) from Xilinx is used for CNN definition on FPGA fabric.

Advanced Computer and Communication Engineering Technology

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Publisher : Springer
ISBN 13 : 3319245848
Total Pages : 1282 pages
Book Rating : 4.3/5 (192 download)

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Book Synopsis Advanced Computer and Communication Engineering Technology by : Hamzah Asyrani Sulaiman

Download or read book Advanced Computer and Communication Engineering Technology written by Hamzah Asyrani Sulaiman and published by Springer. This book was released on 2015-12-28 with total page 1282 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book covers diverse aspects of advanced computer and communication engineering, focusing specifically on industrial and manufacturing theory and applications of electronics, communications, computing and information technology. Experts in research, industry, and academia present the latest developments in technology, describe applications involving cutting-edge communication and computer systems, and explore likely future trends. In addition, a wealth of new algorithms that assist in solving computer and communication engineering problems are presented. The book is based on presentations given at ICOCOE 2015, the 2nd International Conference on Communication and Computer Engineering. It will appeal to a wide range of professionals in the field, including telecommunication engineers, computer engineers and scientists, researchers, academics and students.

In-situ Implementation and Training of Convolutional Neural Network on FPGAs

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ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (12 download)

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Book Synopsis In-situ Implementation and Training of Convolutional Neural Network on FPGAs by : Akshay Raju Krishnani

Download or read book In-situ Implementation and Training of Convolutional Neural Network on FPGAs written by Akshay Raju Krishnani and published by . This book was released on 2020 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: The main objective of this thesis is to investigate the efficiency of in-situ trainable Convolutional Neural Networks (CNNs) on modern programmable System-on-Chip (SoC) Field Programmable Gate Arrays (FPGAs) composed of embedded processors and reconfigurable fabric and to study the robustness of the system when faults happen. One particular characteristic of this work is that CNN is developed exclusively using High-Level Synthesis (HLS), particularly in SystemC, generating Verilog code. In this thesis, the feature maps are also being trained on the FPGA, which is traditionally done offline. The CNN architecture is instantiated on the FPGA and weights are trained through the software model on the ARM processor embedded into the FPGA and updated in the architecture through the AXI bus interface. Moreover, since CNN is implemented in hardware the resource used need to be minimized. This allows to choose a smaller, and cheaper FPGA, as well as reducing the total power consumption. To address this, the effect of bitwidth reduction of the CNN is investigated with respect to the accuracy of handwritten characters recognitions. Finally, the robustness of the CNN is analyzed by breaking internal connection of different neurons studying how the accuracy drops when the fault happens at different layers If the accuracy is reduced, then the CNN is re-trained in-situ to increase the accuracy of the CNN.

OMICS

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Publisher : CRC Press
ISBN 13 : 1439850089
Total Pages : 625 pages
Book Rating : 4.4/5 (398 download)

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Book Synopsis OMICS by : Debmalya Barh

Download or read book OMICS written by Debmalya Barh and published by CRC Press. This book was released on 2011-11-21 with total page 625 pages. Available in PDF, EPUB and Kindle. Book excerpt: A reflection of the explosion of research and development in this field, OMICS: Biomedical Perspectives and Applications explores applications of omics in bioinformatics, cancer research and therapy, diabetes research, plant science, molecular biology, and neurosciences. A select editorial panel of experts discusses their cutting edge omics research and novel technologies, supplying a basic platform of methods and applications and a resource for enhanced cross-pollination in a multiomics approach to future endeavors in the fertile fields of omics research. After an introduction on the omics universe, the book presents modern omics and its applications in nanotechnology, genomics, proteomics, metagenomics, toxicogenomics, immunomics, nutrigenomics, diabetes, neurology, cardiology, and cancer to name just a few. The book begins with an overview of omics and omic technologies such as cellomics, glycomics, and lipidomics. It also discusses bioinformatics, demonstrating how it can be a tool in omics, and examines the various approaches of omics technology in toxicology research and applications in biomedical sciences. While there are a long list of omics books available, most focus narrowly on one area. Presenting a wide view of the current status of integrative omics, this resource contains complete coverage of omics in research and therapy, ranging from neuroscience to cardiology. It collates recent developments in the field into a state-of-the-art framework for this discipline.

FPGA Implementation of Backpropagation Algorithm of Artificial Neural Networks

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Publisher :
ISBN 13 :
Total Pages : 54 pages
Book Rating : 4.:/5 (12 download)

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Book Synopsis FPGA Implementation of Backpropagation Algorithm of Artificial Neural Networks by :

Download or read book FPGA Implementation of Backpropagation Algorithm of Artificial Neural Networks written by and published by . This book was released on 2017 with total page 54 pages. Available in PDF, EPUB and Kindle. Book excerpt: Back-Propagation (BP) Algorithm is one of the efficient learning algorithms for the training of Artificial Neural Networks (ANN). The efficient hardware implementation of the BP Algorithm can find its application in the broad field of applications. The common computing platforms to build the BP algorithm based ANN Systems are Application Specific Integrated Circuits (ASICs) and General-Purpose Processors (GPP) based computers. However, due to a high demand of maintaining a trade-off between performance and flexibility, such computing machines become a bottleneck for further advanced improvements. In the last few decades, there has been significant progress in the field of Field Programmable Gate Arrays (FPGAs), which are based on the reconfigurable hardware platform. One of the main advantages of FPGAs are its flexibility, it is possible to reprogram the same hardware and achieve good performance by allowing parallel computation at the same time. The focus of this thesis is to implement the BP algorithm based ANN system on reconfigurable platform(FPGA). The proposed designs are coded on the software platform, MATLAB and in Verilog Hardware Description Language (Verilog HDL) on FPGA and synthesized on artix-7 FPGA evaluation kit. The validation of the design is verified on two benchmarks and comparisons are observed and discussed between two platforms.

Proceedings

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ISBN 13 :
Total Pages : 530 pages
Book Rating : 4.3/5 (91 download)

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Book Synopsis Proceedings by :

Download or read book Proceedings written by and published by . This book was released on 2002 with total page 530 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Implementation of an FPGA-based Artificial Neural Network

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Publisher :
ISBN 13 :
Total Pages : 33 pages
Book Rating : 4.:/5 (113 download)

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Book Synopsis Implementation of an FPGA-based Artificial Neural Network by : Luya Gao

Download or read book Implementation of an FPGA-based Artificial Neural Network written by Luya Gao and published by . This book was released on 2019 with total page 33 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Design of a Neural Network for FPGA Implementation

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Publisher :
ISBN 13 :
Total Pages : 117 pages
Book Rating : 4.:/5 (96 download)

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Book Synopsis Design of a Neural Network for FPGA Implementation by : Ee Ric Lim

Download or read book Design of a Neural Network for FPGA Implementation written by Ee Ric Lim and published by . This book was released on 2013 with total page 117 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Multimedia, Communication and Computing Application

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Publisher : CRC Press
ISBN 13 : 1315690519
Total Pages : 526 pages
Book Rating : 4.3/5 (156 download)

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Book Synopsis Multimedia, Communication and Computing Application by : Ally Leung

Download or read book Multimedia, Communication and Computing Application written by Ally Leung and published by CRC Press. This book was released on 2015-07-28 with total page 526 pages. Available in PDF, EPUB and Kindle. Book excerpt: 2014 International Conference on Multimedia, Communication and Computing Application (MCCA2014), Xiamen, China, Oct 16-17, 2014, provided a forum for experts and scholars of excellence from all over the world to present their latest work in the area of multimedia, communication and computing applications. In recent years, the multimedia techno

FPGA Implementation of a Wavelet Neural Network with Learning Ability

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Publisher :
ISBN 13 :
Total Pages : 0 pages
Book Rating : 4.:/5 (134 download)

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Book Synopsis FPGA Implementation of a Wavelet Neural Network with Learning Ability by :

Download or read book FPGA Implementation of a Wavelet Neural Network with Learning Ability written by and published by . This book was released on 2006 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: