neural networks and fuzzy logic by vijayalakshmi

Ngày tải lên: 23/03/2014, 22:21

Ngày tải lên: 23/01/2014, 01:20

Ngày tải lên: 18/04/2014, 12:29

... science and engineering: mathematical logic and theorizing followed by experimentation. Neural networks replace these problem solving strategies with trial & error, pragmatic solutions, and a ... improved by a trial -and- error evaluation of small changes to the algorithm's parameters and procedures. This is the strategy of the neural network. Training the Neural Network Neural network ... artificial neural networks to distinguish them from the squishy things inside of animals. However, most scientists and engineers are not this formal and use the term neural network to include both biological...

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Ngày tải lên: 03/04/2014, 12:09

Ngày tải lên: 03/04/2014, 12:09

Ngày tải lên: 23/06/2014, 01:20

Ngày tải lên: 27/06/2014, 00:20

... 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 ... 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...

Ngày tải lên: 13/12/2013, 01:15

... paper by Kalman [1] for the 1 Kalman Filtering and Neural Networks, Edited by Simon Haykin ISBN 0-471-36998-5 # 2001 John Wiley & Sons, Inc. Kalman Filtering and Neural Networks, Edited by Simon ... also the books by Lewis [2] and Grewal and Andrews [3]. The derivation is not only elegant but also highly insightful. Consider a linear, discrete-time dynamical system described by the block diagram ... entries of the matrices F kỵ1;k and H k are all known (i.e., computable), by having ^ xx k and ^ xx À k available at time k. Stage 2 Once the matrices F kỵ1;k and H k are evaluated, they are...

Ngày tải lên: 13/12/2013, 13:15

... themselves altered by misfire, so that normal engine firings followed by misfire may be misinterpreted. We have approached the misfire detection problem with recurrent neural networks trained by GEKF [12] ... KALMAN FILTER TRAINING phenomenon, is particularly troublesome for training of recurrent neural networks and= or neural network controllers, where the temporal order of presentation of data during ... 133– 140. [3] G.V. Puskorius and L. A. Feldkamp, ‘‘ Decoupled extended Kalman filter training of feedforward layered networks, ’’ in Proceedings of International Joint Conference of Neural Networks, Seattle,...

Ngày tải lên: 14/12/2013, 13:15

... circle moving right and up;  square moving right and down;  triangle moving right and up;  circle moving right and down;  square moving right and up;  triangle moving right and down. Training ... 1,1–47 (1991). [2] J.S. Lund, Q. Wu and J.B. Levitt, ‘‘ Visual cortex cell types and connections’’, in M.A. Arbib, Ed., Handbook of Brain Theory and Neural Networks, Cambridge, MA: MIT Press, ... many time steps and anticipate both its shape and location many time steps into the future. 3.2 NEUROBIOLOGICAL AND PERCEPTUAL FOUNDATIONS The architecture of our model is motivated by two key anatomical...

Ngày tải lên: 14/12/2013, 13:15

... by a very small increment, the deviation in 83 Kalman Filtering and Neural Networks, Edited by Simon Haykin ISBN 0-471-36998-5 # 2001 John Wiley & Sons, Inc. Kalman Filtering and Neural Networks, ... illustrated by Packard et al. [3], and then given a firm mathematical foundation by Takens [4] and Man˜e ´ [5]. In essence, the celebrated Takens embedding theorem guaran- tees that by applying ... D.A. Rand and L.S. Young, Eds. Dynamical Systems and Turbulence, Warwick 1980, Lecture Notes in Mathematics Vol. 898. 1981, p. 230. Berlin: Springer-Verlag. [6] A.M. Fraser, ‘‘ Information and...

Ngày tải lên: 14/12/2013, 13:15

... series (a ), the series generated by a neural network trained on x k (b), the series generated by a neural network trained on y k (c ), and the series generated by a neural network trained on y k , ... Atlas, ‘‘Recurrent neural networks and robust time series prediction,’’ IEEE Transactions on Neural Networks, 5(2), 240–254 (1994). [15] S.C. Stubberud and M. Owen, ‘‘Artificial neural network feedback ... shown by the thin curve in Figure 5.3a, is generated by a neural network (10-5-1) with chaotic dynamics, driven by white Gaussian-process noise (s 2 v ẳ 0:36). Colored noise generated by a linear autoregressive...

Ngày tải lên: 14/12/2013, 13:15

... A and B multiplying inputs x and u, respectively; and an output bias vector b, and the noise covariance Q. Each RBF is assumed to be a Gaussian in x space, with center c i and width given by ... sequence of observed data by Y ẳfy 1 ; ; y t g, observed inputs by U ẳfu 1 ; ; u T g, the sequence of hidden variables by X ẳfx 1 ; ; x t g, and the parameters of the model by y.) Maximizing the ... estimation for nonlinear dynamical systems and also as a basis for on-line learning algorithms for feedforward neural networks [15] and radial basis function networks [16, 17]. For more details, see...

Ngày tải lên: 14/12/2013, 13:15

... learning the parameters. The use of the EKF for training neural networks has been developed by Singhal and Wu [8] and Puskorious and Feldkamp [9], and is covered in Chapter 2 of this book. The use of ... time-series estimation with neural networks. Double Inverted Pendulum A double inverted pendulum (see Fig. 7.4) has states corresponding to cart position and velocity, and top and bottom pendulum angle and angular ... chapter reviews this work, and presents extensions to a broader class of nonlinear estimation problems, including nonlinear system identification, training of neural networks, and dual estimation problems....

Ngày tải lên: 14/12/2013, 13:15

... 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 ... 0,7 Figure 11: Comparison of fuzzy logic control versus manual operation. The fuzzy logic controller ensures better capacity usage by operating the process more stable The fuzzy logic load balancing...

Ngày tải lên: 22/12/2013, 10:15