No BSD License
-
bellanim.m
Animation of two generalized bell membership functions.
-
bellmanu.m
Manual tuning of a generalized bell membership funciton.
-
fuzpcr(action)
FUZPCR Fuzzy printed character recognition.
-
hedge(action);
HEDGE Demonstrate effects of linguistic hedges on fuzzy sets
-
mlpdm2(trn_data, mlp_config, ...
MLPDM2 Demo of solving 2-input 1-output problem using MLP with
-
noise2.m
function out_fismat = noise(mf_type, mf_n, dataset)
-
percepdm.m
Demo of perceptron learning
-
printui(arg1,arg2,arg3,arg4,a...
PRINTUI Print figure with uicontrols.
-
siganim.m
Animation of membership functions composed of two sigmoid functions.
-
...
RBFN Radial basis function networks
-
...
RBFN Radial basis function networks
-
[ret,x0,str,ts,xts]=kkk(t,x,u...
KKK is the M-file description of the SIMULINK system named KKK.
-
adjeta(eta, rmse)
ADJETA Adjust learning rate eta in SD according to history of RMSE.
-
adjeta(eta, rmse)
ADJETA Adjust learning rate eta in SD according to history of RMSE.
-
adjkappa(kappa, rmse)
ADJKAPPA Adjust learning rate eta in SD according to history of RMSE.
-
arrow(x, y, s, style)
ARROW Use arrows to plot curves.
-
banana(x, y, mode)
BANANA Rosenbrock's banana function.
-
bit2num(bit, range)
BIT2NUM Conversion from bit string representations to decimal numbers.
-
blackbg
Change figure background to black
-
cartmain(all_trn_data, rule_n...
CARTMAIN Main routine for CART (regression only)
-
channel(in0, in1, in2, in3)
CHANNEL Channel characteristics of equalization problem.
-
chap02
List of plots in chapter 2 of "Neuro-Fuzzy and Soft Computing".
-
chap03
List of plots in chapter 3 of "Neuro-Fuzzy and Soft Computing".
-
chap04
List of plots in chapter 4 of "Neuro-Fuzzy and Soft Computing".
-
chap05
List of plots in chapter 5 of "Neuro-Fuzzy and Soft Computing".
-
chap06
List of plots in chapter 6 of "Neuro-Fuzzy and Soft Computing".
-
chap07
List of plots in chapter 7 of "Neuro-Fuzzy and Soft Computing".
-
chap09
List of plots in chapter 9 of "Neuro-Fuzzy and Soft Computing".
-
chap11
List of plots in chapter 11 of "Neuro-Fuzzy and Soft Computing".
-
chap12
List of plots in chapter 12 of "Neuro-Fuzzy and Soft Computing".
-
chap14
List of plots in chapter 14 of "Neuro-Fuzzy and Soft Computing".
-
chap15
List of plots in chapter 15 of "Neuro-Fuzzy and Soft Computing".
-
chap17
List of plots in chapter 17 of "Neuro-Fuzzy and Soft Computing".
-
chap19
List of plots in chapter 19 of "Neuro-Fuzzy and Soft Computing".
-
cyclesty(H)
Cyclesty Cycle line styles.
-
dec2othe(number, base, digit_...
DEC2OTHE Conversion of decimal to other number representation.
-
defuzzy(x, mf, option)
DEFUZZY Defuzzification of MF.
-
ebr_opti(SNR)
-
ekfmlp(trn_data, mlp_config, ...
SEQMLP On-line extended Kalman filter training for MLP with hyperbolic tangent activation.
-
emdata(data)
EMDATA Error measure of a data set. This is used in CART routine.
-
emnode(node_index)
CARTEM Error measure for a CART node indexed by node_index.
-
entropy(count)
ENTROPY Entropy function, for use as an impurity function in CART.
-
eqtrain(mf_n, mf_type)
-
errmoth(para);
ERRMOTH Error function for fitting the moth data.
-
evaleach(string, bit_n, range...
EVALEACH Evaluation of each individual's fitness value.
-
evalpopu(population, bit_n, r...
EVALPOPU Evaluation of the population's fitness values.
-
exts_mf(x, para)
EXTSMF S-shaped membership function with two or three parameters
-
f_de(position, p1, p2, inv_co...
F_DE Decision function of channel equalization problem.
-
fis(x, y, type)
-
gauss_mf(x, parameter)
GAUSS_MF Gaussian membership function with two parameters.
-
gbell_mf(x, parameter)
GBELL_MF Generalized bell-shaped membership function with three parameters.
-
gd(init_para, x, y)
-
genfig(figTitle)
GENFIG Generates a figure window.
-
getdata(node_index);
GETDATA Get training data of a CART node indexed by node_index.
-
getdata(node_index, data_inde...
SETDATA Set training data of a node in a CART.
-
gini(count)
GINI Gini index function, for use as an impurity function in CART.
-
growtree
GROWTREE Grow tree by splitting a terminal node of a CART.
-
hwmain(case_n, random_seed)
HWMAIN Performance evaluation of MLP learning strategies.
-
hyperf(x, y, mode)
Hyperbolic surface for illustrating steepest descent, Newton,
-
inc_ctrst(mf)
INC_CTRST Contrast intensifier.
-
invsurf
-
kfm(dataID)
KFM Kohonen's feature map with 2-D output units.
-
kfm2(dataID)
KFM2 Kohonen's feature map with 2-D output units.
-
list2cb(list)
-
logmlp(trn_data, mlp_config, ...
TANMLP Steepest descent for MLP with hyperbolic tangent activation.
-
logmlp(trn_data, mlp_config, ...
LOGMLP Steepest descent for MLP with logistic activation.
-
lr_mf(x, parameter)
LR_MF Left-right membership function with 3 parameters.
-
max_star(A, B, star)
MAX_STAR returns the max-star composition of given matrices.
-
mlpdm1(trn_data, mlp_config, ...
MLPDM1 Demo of solving 1-input 1-output problem using MLP with
-
mlpdm1(trn_data, mlp_config, ...
MLPDM1 Demo of solving 1-input 1-output problem using MLP with
-
modmlp(task, mlp_config, trai...
MODMLP
-
modsig(x, parameter)
SIG_MF Sigmoidal membership function with two parameters.
-
nextpopu(popu, fitness, xover...
-
num2bit(x, range)
-
paraf(x, y, mode)
Parabolic surface for illustrating steepest descent, Newton,
-
peaksf(x, y, mode)
Peaks function for illustrating steepest descent, Newton,
-
peaksfcn(input)
-
peaksfcn(input)
PEAKSFCN The PEAKS function.
-
plant(y, u);
-
plotchar(vec)
PLOTCHAR Plots a 35-element vector as a 5x7 grid.
-
plotrule(cart_table, range, n...
PLOTRULE Plot decision boundaries of CART specified by cart_table.
-
pp
PP Pause and prompt.
-
randsrch(fcn, x, bound, max_e...
RANDSRCH Random search method for minimizing a function.
-
randsrch(fcn, x, bound, max_e...
RANDSRCH Random search method for minimizing a function.
-
seqmlp(trn_data, mlp_config, ...
SEQMLP On-line steepest descent for MLP with hyperbolic tangent activation.
-
sig_mf(x, parameter)
SIG_MF Sigmoidal membership function with two parameters.
-
splitnod(node_index)
SPLITNOD Split a CART node indexed by node_index.
-
splitval(trn_data, col)
Find possible split values of a column of a data set. Used in CART.
-
ssc(a, b, p)
SSC Schweizer T-conorm using parameter p.
-
tanmlp(trn_data, mlp_config, ...
TANMLP Steepest descent for MLP with hyperbolic tangent activation.
-
tanmlp(trn_data, mlp_config, ...
TANMLP Steepest descent for MLP with hyperbolic tangent activation.
-
tanmlp(trn_data, mlp_config, ...
TANMLP Steepest descent for MLP with hyperbolic tangent activation
-
trap_mf(x, parameter)
TRAP_MF Trapezoidal membership function with four parameters.
-
tri_mf(x, parameter)
TRI_MF Triangular membership function with three parameters.
-
trn_1in(mf_n, epoch_n)
-
trn_2in(mf_n, epoch_n)
This script requires the Fuzzy Logic Toolbox from the MathWorks.
-
trn_3in(mf_n, epoch_n)
This script requires the Fuzzy Logic Toolbox from the MathWorks.
-
tsc(a, b, p)
TSC Schweizer T-norm using parameter p.
-
tsp(loc)
TSP Traveling salesman problem (TSP) using SA (simulated annealing).
-
uniq(in)
UNIQ Return a vector where neighboring same elements are reduced to
-
usecart(data, CART_table)
USECART Use a CART tree.
-
vecdist(mat1, mat2)
VECDIST Distance between two set of vectors
-
wavefcn(x)
-
activati.m
-
allbells.m
-
allfig.m
-
attract.m
-
bana_sd.m
-
bfgs.m
-
bjpick2.m
-
bjpick3.m
-
bjtrain.m
-
carterr.m
-
cartglob.m
-
cartmf.m
-
cg.m
-
compball.m
-
complv.m
-
contents.m
-
convex.m
-
convexmf.m
-
cooldemo.m
-
cri.m
-
cyl_ext.m
-
decsurf1.m
-
descent.m
-
dfp.m
-
difflr.m
-
disp_mf.m
-
disp_sig.m
-
dryarx.m
-
drydata.m
-
drypick.m
-
drypick2.m
-
drypick3.m
-
drypick4.m
-
drytrain.m
-
equdata.m
-
equdec.m
-
equdensi.m
-
extensio.m
-
fcn.m
-
fitcurve.m
-
fitmoth.m
-
fitpeaks.m
-
ftsurf1.m
-
ftsurf2.m
-
fuzimp.m
-
fuzsetop.m
-
gdconv.m
-
gdss1.m
-
gdss2.m
-
getauto.m
-
gmp.m
-
gmt.m
-
go_cart.m
-
go_ga.m
-
go_icec1.m
-
go_icec2.m
-
go_inv.m
-
go_rand.m
-
go_rand_.m
-
go_simp.m
-
go_simp_.m
-
hem.m
-
houdata.m
-
houpick.m
-
houpick1.m
-
houpick2.m
-
houpick3.m
-
houpick4.m
-
houtrain.m
-
idpick3.m
-
idpick4.m
-
impurity.m
-
init_mf.m
-
intensif.m
-
inv_fc.m
-
inv_sig.m
-
lingmf.m
-
lmsaddle.m
-
loadmpg.m
-
lv.m
-
lvqdata.m
-
mam1.m
-
mam2.m
-
mf2d.m
-
mf_univ.m
-
mount1.m
-
mount2.m
-
mpgdata.m
-
mpgpick.m
-
mpgpick2.m
-
mpgpick3.m
-
mpgpick4.m
-
mpgsurf.m
-
mpgtrain.m
-
negation.m
-
newimpur.m
-
newton.m
-
nlsebox.m
-
nndemo.m
-
noise1.m
-
nonoise.m
-
optideci.m
-
optiplot.m
-
pchar.m
-
plot_ebr.m
-
project.m
-
rbfndm1.m
-
rbfnxor.m
-
rbfnxor1.m
-
rbfnxor2.m
-
resolut.m
-
saddle.m
-
saddle1.m
-
saddle2.m
-
sddemo.m
-
show_nfc.m
-
showdata.m
-
softdemo.m
-
splits.m
-
spring.m
-
spring1.m
-
sstnorm.m
-
startup.m
-
stitch.m
-
subset.m
-
sug1.m
-
sug2.m
-
taylor.m
-
tconorm.m
-
tnorm.m
-
transfor.m
-
trn_4in.m
-
trn_inv.m
-
tsu1.m
-
tsurf1.m
-
tsurf2.m
-
ttt.m
-
verify.m
-
xor2dmf.m
-
xordata.m
-
xorfis.m
-
xormf.m
-
xorsurf.m
-
xorsurf1.m
-
xorsurf2.m
-
slmg1
-
View all files
|
|
| plant(y, u); |
function out = plant(y, u);
%out = y*u/(1+y^2)-sin(u); % no good
%out = 0.8*sin(2*y)+1.2*u; % fine
out = y*u/(1+y^2)-tan(u); % fine
|
|
Contact us at files@mathworks.com
