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ویرایش:
نویسندگان: The MathWorks. Inc.
سری:
ناشر: The MathWorks, Inc.
سال نشر: 2021
تعداد صفحات: 278
زبان: English
فرمت فایل : PDF (درصورت درخواست کاربر به PDF، EPUB یا AZW3 تبدیل می شود)
حجم فایل: 8 مگابایت
در صورت تبدیل فایل کتاب MATLAB Deep Learning HDL Toolbox UG. به فرمت های PDF، EPUB، AZW3، MOBI و یا DJVU می توانید به پشتیبان اطلاع دهید تا فایل مورد نظر را تبدیل نمایند.
توجه داشته باشید کتاب MATLAB Deep Learning HDL Toolbox UG. نسخه زبان اصلی می باشد و کتاب ترجمه شده به فارسی نمی باشد. وبسایت اینترنشنال لایبرری ارائه دهنده کتاب های زبان اصلی می باشد و هیچ گونه کتاب ترجمه شده یا نوشته شده به فارسی را ارائه نمی دهد.
What is Deep Learning? Introduction to Deep Learning Training Process Training from Scratch Transfer Learning Feature Extraction Convolutional Neural Networks Deep Learning Processor Deep Learning Processor Architecture DDR External Memory Generic Convolution Processor Activation Normalization Conv Controller (Scheduling) Generic FC Processor FC Controller (Scheduling) Deep Learning Processor Applications Applications and Examples MATLAB Controlled Deep Learning Processor Deep Learning on FPGA Overview Deep Learning on FPGA Workflow Deep Learning on FPGA Solution and Workflows FPGA Advantages Deep Learning on FPGA Workflows Workflow and APIS Prototype Deep Learning Networks on FPGA and SoCs Workflow Profile Inference Run Multiple Frame Support Input DDR Format Output DDR Format Manually Enable Multiple Frame Mode Fast MATLAB to FPGA Connection Using LIBIIO/Ethernet LIBIIO/Ethernet Connection Based Deployment Ethernet Interface Configure your LIBIIO/Ethernet Connection LIBIIO/Ethernet Performance Networks and Layers Supported Networks, Layers, Boards, and Tools Supported Pretrained Networks Supported Layers Supported Boards Third-Party Synthesis Tools and Version Support Custom Processor Configuration Workflow Custom Processor Configuration Workflow Estimate Performance of Deep Learning Network Estimate Performance of Custom Deep Learning Network for Custom Processor Configuration Evaluate Performance of Deep Learning Network on Custom Processor Configuration Estimate Resource Utilization for Custom Processor Configuration Estimate Resource Utilization Customize Bitstream Configuration to Meet Resource Use Requirements Effects of Custom Deep Learning Processor Parameters on Performance and Resource Utilization Custom Processor Code Generation Workflow Generate Custom Bitstream Intel Bitstream Resource Utilization Xilinx Bitstream Resource Utilization Generate Custom Processor IP Featured Examples Get Started with Deep Learning FPGA Deployment on Intel Arria 10 SoC Get Started with Deep Learning FPGA Deployment on Xilinx ZCU102 SoC Logo Recognition Network Deploy Transfer Learning Network for Lane Detection Image Category Classification by Using Deep Learning Defect Detection Profile Network for Performance Improvement Bicyclist and Pedestrian Classification by Using FPGA Visualize Activations of a Deep Learning Network by Using LogoNet Authoring a Reference Design for Live Camera Integration with Deep Learning Processor IP Core Run a Deep Learning Network on FPGA with Live Camera Input Running Convolution-Only Networks by using FPGA Deployment Accelerate Prototyping Workflow for Large Networks by using Ethernet Create Series Network for Quantization Vehicle Detection Using YOLO v2 Deployed to FPGA Custom Deep Learning Processor Generation to Meet Performance Requirements Deploy Quantized Network Example Quantize Network for FPGA Deployment Evaluate Performance of Deep Learning Network on Custom Processor Configuration Customize Bitstream Configuration to Meet Resource Use Requirements Vehicle Detection Using DAG Network Based YOLO v2 Deployed to FPGA Customize Bitstream Configuration to Meet Resource Use Requirements Image Classification Using DAG Network Deployed to FPGA Classify Images on an FPGA Using a Quantized DAG Network Classify ECG Signals Using DAG Network Deployed To FPGA Deep Learning Quantization Quantization of Deep Neural Networks Precision and Range Histograms of Dynamic Ranges Quantization Workflow Prerequisites Calibration Workflow Validation Workflow Code Generation and Deployment Deep Learning Processor IP Core User Guide Deep Learning Processor IP Core Use Compiler Output for System Integration External Memory Address Map Compiler Optimizations Leg Level Compilations External Memory Data Format Key Terminology Convolution Module External Memory Data Format Fully Connected Module External Memory Data Format Deep Learning Processor Register Map