Practical Neural Network Recipes in C++Morgan Kaufmann, 1993 - 493 Seiten This text serves as a cookbook for neural network solutions to practical problems using C++. It will enable those with moderate programming experience to select a neural network model appropriate to solving a particular problem, and to produce a working program implementing that network. The book provides guidance along the entire problem-solving path, including designing the training set, preprocessing variables, training and validating the network, and evaluating its performance. Though the book is not intended as a general course in neural networks, no background in neural works is assumed and all models are presented from the ground up. The principle focus of the book is the three layer feedforward network, for more than a decade as the workhorse of professional arsenals. Other network models with strong performance records are also included. Bound in the book is an IBM diskette that includes the source code for all programs in the book. Much of this code can be easily adapted to C compilers. In addition, the operation of all programs is thoroughly discussed both in the text and in the comments within the code to facilitate translation to other languages. |
Inhalt
III | 2 |
IV | 3 |
V | 4 |
VI | 6 |
VII | 8 |
VIII | 9 |
IX | 10 |
X | 15 |
LXXV | 220 |
LXXVI | 221 |
LXXVII | 223 |
LXXVIII | 226 |
LXXIX | 227 |
LXXX | 229 |
LXXXI | 231 |
LXXXII | 232 |
XI | 16 |
XII | 18 |
XIII | 21 |
XIV | 23 |
XV | 24 |
XVI | 29 |
XVII | 31 |
XVIII | 32 |
XIX | 40 |
XX | 41 |
XXI | 44 |
XXII | 47 |
XXIII | 49 |
XXIV | 50 |
XXV | 61 |
XXVI | 62 |
XXVII | 64 |
XXVIII | 67 |
XXIX | 68 |
XXX | 72 |
XXXI | 74 |
XXXII | 77 |
XXXIII | 78 |
XXXIV | 85 |
XXXV | 90 |
XXXVI | 94 |
XXXVII | 100 |
XXXVIII | 111 |
XXXIX | 116 |
XL | 117 |
XLI | 119 |
XLII | 121 |
XLIII | 122 |
XLIV | 126 |
XLV | 128 |
XLVI | 132 |
XLVII | 135 |
XLVIII | 136 |
XLIX | 138 |
L | 140 |
LI | 144 |
LII | 147 |
LIII | 148 |
LIV | 149 |
LV | 155 |
LVI | 157 |
LVII | 165 |
LVIII | 166 |
LIX | 167 |
LX | 169 |
LXI | 173 |
LXII | 174 |
LXIII | 176 |
LXIV | 180 |
LXV | 187 |
LXVII | 190 |
LXVIII | 191 |
LXIX | 201 |
LXX | 202 |
LXXI | 208 |
LXXII | 209 |
LXXIII | 211 |
LXXIV | 219 |
LXXXIII | 235 |
LXXXIV | 239 |
LXXXV | 242 |
LXXXVI | 245 |
LXXXVII | 246 |
LXXXVIII | 249 |
LXXXIX | 250 |
XC | 251 |
XCII | 253 |
XCIII | 254 |
XCIV | 255 |
XCV | 266 |
XCVI | 267 |
XCVII | 270 |
XCVIII | 274 |
XCIX | 276 |
C | 279 |
CI | 281 |
CII | 282 |
CIII | 283 |
CIV | 284 |
CV | 290 |
CVI | 292 |
CVII | 295 |
CVIII | 299 |
CIX | 300 |
CX | 303 |
CXI | 316 |
CXII | 319 |
CXIII | 327 |
CXIV | 330 |
CXV | 332 |
CXVI | 340 |
CXVII | 343 |
CXVIII | 344 |
CXX | 347 |
CXXI | 348 |
CXXII | 351 |
CXXIII | 359 |
CXXIV | 361 |
CXXV | 362 |
CXXVI | 367 |
CXXVII | 368 |
CXXVIII | 369 |
CXXIX | 370 |
CXXX | 371 |
CXXXI | 376 |
CXXXII | 381 |
CXXXIII | 382 |
CXXXIV | 384 |
CXXXV | 389 |
CXXXVI | 403 |
CXXXVII | 405 |
CXXXVIII | 406 |
CXL | 409 |
CXLI | 412 |
CXLIII | 413 |
CXLIV | 417 |
CXLV | 423 |
CXLVI | 479 |
491 | |
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Häufige Begriffe und Wortgruppen
activation actual algorithm alternative annealing applied approach approximately called chapter choice CLASSIFY coefs collection complete computed confidence cost decision define direction discussed distribution double effect equal error estimate example expected extremely feedforward network Figure filter final fitness FREE fuzzy set genetic given gradient hidden layer hidden neurons hypothesis important improved individual initial input iteration later learning length less limit mean measure membership function method minimize neural network normal NULL operation optimization output neuron parameter pattern performance population possible practical prediction presented probability problem produce random reason regression relative represented routine rule sample scaling shown simple single square step Suppose temperature threshold training set usually variable vector void weights zero
Verweise auf dieses Buch
Neural Networks: An Introduction Berndt Müller,Joachim Reinhardt,Michael T. Strickland Eingeschränkte Leseprobe - 1995 |
Data Analysis for Chemists: Applications to QSAR and Chemical Product Design David Livingstone Keine Leseprobe verfügbar - 1995 |