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Highlights from
Neural Networks: A Comprehensive Foundation, 2e book Companion Software

• A=bpm_dec_bnds(W1, b1, W2, b2...
• B=colmult(A, vec)
• B=sgn(A) function B=sgn(A)
• C=mk_data(pats) function C=mk_data(pats)
• D=gha_chopstak(P,rm,cm) function D=gha_chopstak(P,rm,cm)
• I=gha_recompose(coeffs,W,mval) I=recompose(coeffs,W,mval)
• I=gha_unchopst(X,r,c,rm,cm) function I=gha_unchopst(X,r,c,rm,cm)
• K=gha_dispwe(W,j) function K=gha_dispwe(W,j)
• M=thresh(A,ll,ul)
• W=gha(P,epochs,m,beta,W) function W=gha(P,epochs,m,beta,W)
• W=gha_getweights(Image,epochs...
• W=hop_stor(P) function W=hop_stor(P)
• [P, flip]=hop_flip(P, prob, s...
• [W1, b1, W2, b2, ep_err, init...
• [W_out, p_out]=som_1d(P, nsof...
• [W_out, p_out]=som_2d(P, nsof...
• [cor, uncor, O, dec]=bpm_test...
• [pesos,vect,b]=svm_rbf2(datos... % [pesos,vect,b]=svm_rbf(datos,escala,niter,cad,restric);
• [s, count, M]=hop_test(W,x,up...
• b=phi(a)
• b=phi_d(a)
• c=bsb(x,beta,multi) function c=bsb(x,beta)
• coeffs=gha_getcoeffs(Orig,W,p... function coeffs=gha_getcoeffs(Orig,W,plot_flg)
• gha_quantcoeffs(C,W,O,n)
• hop_plotdig(P,r,c,stri) function hop_plotdig(P,r,c)
• hop_plotpats(P) function hop_plotpats(P)
• out=pl_circ(cen, radius, res,... function out=pl_circ(cen, radius, res, plot_flag)
• p=rbf_correct(y,d) p - percent correct in two class problem
• pim(Z) function pim(Z)
• rbf(x, t, d, sigma, lam)
• rbf_db(w, t, sigma, st_sz)
• rbf_mkGF(x,t)
• rbf_test(w, x, t, sigma)
• shuffle(n1,n2,n3,n4,n5)
• som_pl_map(A,p1,p2, P1, P2) function som_pl_map(A,p1,p2)
• svm_dec_bnd(pesos, vect, b, e... function svm_dec_bnd(pesos, vect, b, escala)
• svm_test(data, pesos, vect, b...
• y=proymayor(x,threshold,relax)
• y=proymenor(x,threshold,relax)
• hop_demo.m
• ica.m
• som_2d_demo.m
• View all files