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找到约 10,000 项符合「self」的源代码

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热门代码： main.c GPIO I2C SPI UART timer interrupt ADC PWM LED
www.eeworm.com/read/141297/5773874

py qa_hilbert.py

#!/usr/bin/env python # # Copyright 2004 Free Software Foundation, Inc. # # This file is part of GNU Radio # # GNU Radio is free software; you can redistribute it and/or modify # it under the terms
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www.eeworm.com/read/141297/5773876

py qa_message.py

#!/usr/bin/env python # # Copyright 2004 Free Software Foundation, Inc. # # This file is part of GNU Radio # # GNU Radio is free software; you can redistribute it and/or modify # it under the terms
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www.eeworm.com/read/141297/5773882

py qa_nlog10.py

#!/usr/bin/env python # # Copyright 2005 Free Software Foundation, Inc. # # This file is part of GNU Radio # # GNU Radio is free software; you can redistribute it and/or modify # it under the terms
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www.eeworm.com/read/141297/5773885

py qa_head.py

#!/usr/bin/env python # # Copyright 2004 Free Software Foundation, Inc. # # This file is part of GNU Radio # # GNU Radio is free software; you can redistribute it and/or modify # it under the terms
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www.eeworm.com/read/141297/5773898

py seq_with_cursor.py

# # Copyright 2003,2004 Free Software Foundation, Inc. # # This file is part of GNU Radio # # GNU Radio is free software; you can redistribute it and/or modify # it under the terms of the GNU Genera
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www.eeworm.com/read/140847/5779250

m tabular_kernel.m

function K = tabular_kernel(fg, self) % TABULAR_KERNEL Make a table-based local kernel (discrete potential) % K = tabular_kernel(fg, self) % % fg is a factor graph % self is the number of a representa
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www.eeworm.com/read/140847/5779303

m log_prob_node.m

function L = log_prob_node(CPD, self_ev, pev) % LOG_PROB_NODE Compute prod_m log P(x(i,m)| x(pi_i,m), theta_i) for node i (gaussian) % L = log_prob_node(CPD, self_ev, pev) % % self_ev(m) is the eviden
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www.eeworm.com/read/140847/5779359

m gmux_cpd.m

function CPD = gmux_CPD(bnet, self, varargin) % GMUX_CPD Make a Gaussian multiplexer node % % CPD = gmux_CPD(bnet, node, ...) is used similarly to gaussian_CPD, % except we assume there is exactly one
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www.eeworm.com/read/140847/5779373

m mlp_cpd.m

function CPD = mlp_CPD(bnet, self, nhidden, w1, b1, w2, b2, clamped, max_iter, verbose, wthresh, llthresh) % MLP_CPD Make a CPD from a Multi Layer Perceptron (i.e., feedforward neural network) % %
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www.eeworm.com/read/140847/5779384

m softmax_cpd.m

function CPD = softmax_CPD(bnet, self, varargin) % SOFTMAX_CPD Make a softmax (multinomial logit) CPD % % To define this CPD precisely, let W be an (m x n) matrix with W(i,:) = {i-th row of B} % => w
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