代码搜索：Inference
找到约 1,820 项符合「Inference」的源代码
代码结果 1,820
www.eeworm.com/read/160391/5571474
m hmm_2tbn_inf_engine.m
function engine = hmm_2TBN_inf_engine(bnet, varargin)
% HMM_2TBN_INF_ENGINE Inference engine for DBNs which uses the forwards-backwards algorithm.
% engine = hmm_2TBN_inf_engine(bnet, ...)
%
% The
www.eeworm.com/read/160391/5571566
m set_params.m
function engine = set_params(engine, varargin)
% SET_PARAMS Modify parameters of the inference engine
% engine = set_params(engine, 'param1',val1, 'param2',val2, ...)
%
% Parameter names are liste
www.eeworm.com/read/154079/5642581
prj proj.prj
#-- Synplicity, Inc.
#-- Version 7.0.3
#-- Project file G:\XROADS\INFERENCE_STATUS\SPRO_703\VERILOG\BUFGMUX_INSTANCIATE\proj.prj
#-- Written on Thu Feb 14 15:57:46 2002
#add_file options
a
www.eeworm.com/read/154079/5642586
prj proj.prj
#-- Synplicity, Inc.
#-- Version 7.0.3
#-- Project file G:\XROADS\INFERENCE_STATUS\SPRO_703\VERILOG\DCM_INSTANCIATE\FREQUENCY_SYNTHESIS\proj.prj
#-- Written on Thu Feb 14 15:57:03 2002
#add
www.eeworm.com/read/172172/9722112
m bay_rr.m
function [A,B,C,D,E,F,G] = bay_rr(X,Y,gam,level,nb,eigvals,eigvec)
% Bayesian inference of the cost on the three levels of linear ridge regression
%
% >> cost = bay_rr(X, Y, gam, level)
%
% This fun
www.eeworm.com/read/367440/9748480
m bay_rr.m
function [A,B,C,D,E,F,G] = bay_rr(X,Y,gam,level,nb,eigvals,eigvec)
% Bayesian inference of the cost on the three levels of linear ridge regression
%
% >> cost = bay_rr(X, Y, gam, level)
%
% This fun
www.eeworm.com/read/291453/8417535
vhd 各种功能的计数器.vhd
-- MAX+plus II VHDL Example
-- Efficient Counter Inference
-- Copyright (c) 1994 Altera Corporation
-- download from:www.pld.com.cn & www.fpga.com.cn
Library IEEE ;
use IEEE.std_logic_1164.all
www.eeworm.com/read/291453/8417585
vhd 带load、clr等功能的寄存器.vhd
-- Register Inference
-- Download from: http://www.fpga.com.cn
Library IEEE ;
use IEEE.std_logic_1164.all ;
ENTITY reginf IS
PORT
(
d, clk, clr, pre, load, data : IN BIT;
q1, q2,
www.eeworm.com/read/428451/8867318
m bay_lssvm.m
function [A,B,C,D,E] = bay_lssvm(model,level,type, nb, bay)
% Compute the posterior cost for the 3 levels in Bayesian inference
%
% >> cost = bay_lssvm({X,Y,type,gam,sig2}, level, type)
% >> cost = b
www.eeworm.com/read/427586/8932180
m bay_lssvm.m
function [A,B,C,D,E] = bay_lssvm(model,level,type, nb, bay)
% Compute the posterior cost for the 3 levels in Bayesian inference
%
% >> cost = bay_lssvm({X,Y,type,gam,sig2}, level, type)
% >> cost = b