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Import and export Darknet models(https://github.com/pjreddie/darknet ) within MATLAB deep learning networks. The importer can import all the seriesNetworks in the darknet and some simple DAGnetworks. The exporter can export all the seriesNetworks and some of the backbone networks. In addition to importing the deep neural network, the importer can obtain the feature map size of the network, the n

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This book details the significant performance tradeoffs available in analog CMOS design and guides the designer towards optimum design by describing: An interpretation of MOS modeling for the analog designer, motivated by the EKV MOS model, using tabulated hand expressions and figures that give performance and tradeoffs for the design choices of drain current, inversion coefficient, and channel length; performance includes effective gate-source bias and drain-source saturation voltages, transconductance efficiency, transconductance distortion, normalized drain-source conductance, capacitances, gain and bandwidth measures, thermal and flicker noise, mismatch, and gate and drain leakage current Measured data that validates the inclusion of important small-geometry effects like velocity saturation, vertical-field mobility reduction, drain-induced barrier lowering, and inversion-level increases in gate-referred, flicker noise voltage In-depth treatment of moderate inversion, which offers low bias compliance voltages, high transconductance efficiency, and good immunity to velocity saturation effects for circuits designed in modern, low-voltage processes Fabricated design examples that include operational transconductance amplifiers optimized for various tradeoffs in DC and AC performance, and micropower, low-noise preamplifiers optimized for minimum thermal and flicker noise A design spreadsheet, available at the book web site, that facilitates rapid, optimum design of MOS devices and circuits

关于神经网络训练技巧的论文集，设计训练过程的各个方面