代码搜索:recursive

找到约 2,177 项符合「recursive」的源代码

代码结果 2,177
www.eeworm.com/read/192735/8289569

m rspregtrain.m

function [alpha_fin,b_fin] = rsptrain(K,Y,C,epsilon,T,S_min), % Recursive Stabilization Procedure %% Variable Description %% %% m = size(K,1); k = ceil(log(m/S_min)/log(T/(T-1))); current_position =
www.eeworm.com/read/459616/7270456

cpp rvbits.cpp

// recursive dynamic programming image compression #include int L = 256, header = 11; int kay[6]; int l[6] = {0, 6, 3, 10, 2, 3}; int b[6] = {0, 1, 2, 3, 2, 1}; int n = 5; int S(int i)
www.eeworm.com/read/197407/7998061

cpp rknap1.cpp

// dynamic programming recursive knapsack #include #include "make2db.h" int p[6] = {0, 6, 3, 5, 4, 6}; int w[6] = {0, 2, 2, 6, 5, 4}; int x[6]; int **D; int n = 5; int c = 1
www.eeworm.com/read/147682/5728148

m init_sharf.m

% [u,w,e,c,d,mu,Px,Py]=init_sharf(N,M,L,u0,w0,e0,c0,d0,mu0) % % Creates and initializes the variables required for the % Simple Hyperstable Adaptive Recursive Filter (SHARF) % algorithm
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m init_rlslbpef.m

% [ff,bb,fb,cf,b,y,e,kf,kb,x] = init_rlslbpef(L,ff0,bb0,fb0,cf0,b0,x0) % % Creates and initializes the variables required for the % Recursive Least Squares Lattice Backward Predictor Error
www.eeworm.com/read/208657/15239757

m rarx4.m

function [th,datan]=rarx4(y,u,mxs,adm,adg,data0) % [th,datan]=rarx4(y,u,mxs,adm,adg,data0) MIMO model obtained joining % all the MISO recursive arx models between inputs and each output. % Each
www.eeworm.com/read/38039/1093255

mnu asmregopt.mnu

ASM#REG#OPT 装配再生选项 # remove the # sign and enter foreign help string in this line Recursive 递归 Regenerate the part's references before regenerating part itself. 在再生零件本身之前再生此零件的参照。 Simple 简单 Do not re
www.eeworm.com/read/180227/5287795

makefile

include ../../rtl.mk ifneq ($(wildcard $(RTL_DIR)/.config),) include $(RTL_DIR)/.config endif EX = nanosleep.o EX += create_recursive.o print_mod.o print_app EX += posix_mod.o posix_app ifdef CONFI
www.eeworm.com/read/472861/6858998

m rarx3.m

function [th,datan]=rarx3(y,u,adm,adg,data0) % [th,datan]=rarx3(y,u,adm,adg,data0) MIMO model obtained joining % all the MISO recursive arx models between inputs and each output. % Each rarx mod
www.eeworm.com/read/192735/8289509

m rsptrain.m

function [alpha_fin,b_fin] = rsptrain(K,Y,C,T,S_min), % Recursive Stabilization Procedure %% Variable Description %% %% m = size(K,1); k = ceil(log(m/S_min)/log(T/(T-1))); current_position = [0,0]; N