neural networks fuzzy logic and genetic algorithms by rajasekaran

... representation of fuzzy logic with the learning power of neural nets, and you get NeuroFuzzy. Training Fuzzy Logic Systems with NeuroFuzzy Many alternative ways of integrating neural nets and fuzzy logic have ... sets", Fuzzy Sets and Systems, 2, p. 173-186. Figure 14: NeuroFuzzy technologies map a neural net to a fuzzy logic system enabling neural net learning algorithms to be used with fuzzy logic system ... nets and fuzzy logic have its strengths and weaknesses In simple words, both neural nets and fuzzy logic are powerful design techniques that have its strengths and weaknesses. Neural nets can...

Ngày tải lên: 13/12/2013, 01:15

... representation of fuzzy logic with the learning power of neural nets, and you get NeuroFuzzy. Training Fuzzy Logic Systems with NeuroFuzzy Many alternative ways of integrating neural nets and fuzzy logic have ... nets and fuzzy logic have its strengths and weaknesses In simple words, both neural nets and fuzzy logic are powerful design techniques that have its strengths and weaknesses. Neural nets can ... sway minimization is Figure 14: NeuroFuzzy technologies map a neural net to a fuzzy logic system enabling neural net learning algorithms to be used with fuzzy logic system design If the error back...

Ngày tải lên: 22/12/2013, 10:15

Ngày tải lên: 07/03/2014, 13:20

... impulses and arbitrary delays. This class of generalized neural networks include many continuous or discrete time neural networks such as, Hopfield type neural networks, cellular neural networks, ... Cohen-Grossberg neural networks, and so on. To the best of our knowledge, the known results about the existence of anti-periodic solutions for neural networks are all done by a similar analytic method, and ... 0, ∞. System 1.1 includes many neural continuous and discrete time networks 1–9. For examples, the high-order Hopfield neural networks with impulses and delays see 8: x  i  t  ...

Ngày tải lên: 21/06/2014, 07:20

... Artificial Neural Networks - Application 338 2. Neural network architecture and learning algorithms Fig. 1.1a. An m-layer feedforward neural network Fig. 1.1b. Weights and biases ... Confidence Intervals for Neural Networks and Applications to Modeling Engineering Materials 339 2.1 Architecture of feedforward neural networks A feedforward neural network is a massive ... structure of feedforward neural networks and basic learning algorithms. Then, nonlinear regression and its implementation within the nonlinear structure like a feedforward neural network will be...

Ngày tải lên: 29/06/2014, 13:20

... f i and h i+1 = h i + v i (for cycle calculating). ALGEBRAIC APROACH TO MEANING OF ALGEBRAIC APROACH TO MEANING OF LINGUISTIC TERMS, FUZZY LOGIC AND LINGUISTIC TERMS, FUZZY LOGIC AND ... at 0.96 and M at 0.64; Velocity v fires only DS at 0.58 and DL at 0.42. L (.96) AND DS (.58) ⇒ DS (.58); L (.96) AND DL (.42) ⇒ Z (.42) M (.64) AND DS (.58) ⇒ Z (.58) ; M (.64) AND DL ... variables X j and Y linguistically: If X 1 = A 11 and and X m = A 1m then Y = B 1 . . . . . . . . . . . . . . . . If X 1 = A n1 and and X m = A nm then Y = B n It is called a fuzzy model...

Ngày tải lên: 01/07/2014, 12:33

... 0 C++ Neural Networks and Fuzzy Logic: Preface Binary and Bipolar Inputs 27 Chapter 3—A Look at Fuzzy Logic Crisp or Fuzzy Logic? Fuzzy Sets Fuzzy Set Operations Union of Fuzzy Sets Intersection and ... Input Vectors Example Variations and Applications of Kohonen Networks C++ Neural Networks and Fuzzy Logic: Preface Preface 8 C++ Neural Networks and Fuzzy Logic by Valluru B. Rao MTBooks, IDG Books ... software reuse and enhanced reliability. Previous Table of Contents Next Copyright â IDG Books Worldwide, Inc. C++ Neural Networks and Fuzzy Logic: Preface Summary 37 C++ Neural Networks and Fuzzy Logic by...

Ngày tải lên: 23/03/2014, 22:21

... ISRR-ANN 4-5-1, and ISRR-ANN 4-7-7-1 models are 95.78%, 95.87%, and 99.27%, respectively. 16.5.2 Conclusions The fuzzy logic and neural- networks- based ISRR models demonstrated that learning and reasoning capabilities ... train the fuzzy system by generating fuzzy rules from input–output pairs, and combining these generated and linguistic rules into a common fuzzy rule base. After input vectors were fuzzified by the ... methodologies are artificial neural networks (ANN) and fuzzy neural (FN) systems. An overview of these two approaches follows in the next section. 16.2.1 Neural Networks Model Several learning...

Ngày tải lên: 23/01/2014, 01:20

... complexity analysis 98 Fuzzy logic fundamentals Historical review Fuzzy sets and fuzzy logic 114 Types of membership functions 116 Linguistic variables 117 Fuzzy logic operators 117 Fuzzy control ... electric drives/power systems and a summary description of neural networks, fuzzy logic, electronic design automation (EDA) techniques, ASICs/FPGAs and VHDL. The aspects covered allow a basic understanding of the ... Xilinx FPGAs and comprehensively tested by simulation and experimental measurements. This book brings together the complex features of control strategies, EDA, neural networks, fuzzy logic, electric...

Ngày tải lên: 18/04/2014, 12:29

... interest. 4 Microcalcification classification by ANN Artificial neural networks (ANNs) are biologically inspired networks based on the neuron organization and decision-making process of the human ... feature extraction, clustering by the k-means algorithm for MC detection and, finally, using feature selection and a clas- sifier based on a general regression neural network (GRNN) and multilayer perceptron ... fundamental mor- phological operations are erosion and dilation. The contrast can be defined as the difference in inten- sity between an image structure and its background. By combining morphological operations,...

Ngày tải lên: 20/06/2014, 22:20

... K. Jain and J. Mao, Eds., “Special issue on artificial neural networks and statistical pattern recognition,” IEEE Transac- tions on Neural Networks, vol. 8, no. 1, 1997. [12] A. Baraldi and N. ... and I. W. Sandberg, “Universal approximation using radial-basis-function networks, ” Neural Computation, vol. 5, no. 2, pp. 305–316, 1993. [16] D. F. Specht, “Probabilistic neural networks, ” Neural ... Department of Electrical En- gineering and Elect ronics, University of Liverpool, Liverpool, England, UK, 2000. [22] L. B. Jack and A. K. Nandi, Genetic algorithms for feature extraction in machine...

Ngày tải lên: 23/06/2014, 01:20

Ngày tải lên: 27/06/2014, 00:20

Ngày tải lên: 28/06/2014, 14:20

... A. Neural networks : algorithms, applications, and programming techniques / James A. Freeman and David M. Skapura. p. cm. Includes bibliographical references and index. ISBN 0-201-51376-5 1. Neural ... group on neural networks, which has its own periodical. The primary conference in the United States is the International Joint Con- ference on Neural Networks, sponsored by the IEEE and INNS. This ... adapt themselves to model a topological mapping accurately, and even networks that can learn to recognize and reproduce a temporal sequence of patterns. All these networks are based on the simple...

Ngày tải lên: 06/07/2014, 15:20

... such as the visual cortex, as well as studying and implementing simple resistive networks for computing motion, stereo, and color in biological and artificial systems. 1.1 Elementary Neurophysiology 13 Figure ... in (a) and (b) are the concepts of divergence and convergence. Shown in (b), (c), and (d) are examples of circuits with feedback paths. the action of certain networks using propositional logic. ... actually modeling the brain. We prefer to say that these networks have been inspired by our current understanding of neurophysiology. On the other hand, it is often too easy for engineers, in their...

Ngày tải lên: 06/07/2014, 15:23

Ngày tải lên: 12/08/2014, 21:21

Ngày tải lên: 12/08/2014, 21:21

Ngày tải lên: 12/08/2014, 21:21