By Cornelius T. Leondes

ISBN-10: 0080498981

ISBN-13: 9780080498980

ISBN-10: 012443861X

ISBN-13: 9780124438613

This quantity is the 1st assorted and finished therapy of algorithms and architectures for the conclusion of neural community platforms. It provides suggestions and various tools in several parts of this vast topic. The booklet covers significant neural community platforms buildings for reaching powerful structures, and illustrates them with examples. This quantity contains Radial foundation functionality networks, the Expand-and-Truncate studying set of rules for the synthesis of Three-Layer Threshold Networks, weight initialization, quickly and effective versions of Hamming and Hopfield neural networks, discrete time synchronous multilevel neural structures with diminished VLSI calls for, probabilistic layout ideas, time-based strategies, suggestions for lowering actual attention requisites, and functions to finite constraint difficulties. a special and accomplished reference for a huge array of algorithms and architectures, this booklet may be of use to practitioners, researchers, and scholars in business, production, electric, and mechanical engineering, in addition to in machine technological know-how and engineering. Key good points* Radial foundation functionality networks* The Expand-and-Truncate studying set of rules for the synthesis of Three-Layer Threshold Networks* Weight initialization* quick and effective versions of Hamming and Hopfield neural networks* Discrete time synchronous multilevel neural structures with diminished VLSI calls for* Probabilistic layout options* Time-based options* thoughts for lowering actual recognition specifications* functions to finite constraint difficulties* useful recognition equipment for Hebbian variety associative reminiscence structures* Parallel self-organizing hierarchical neural community structures* Dynamics of networks of organic neurons for usage in computational neurosciencePractitioners, researchers, and scholars in business, production, electric, and mechanical engineering, in addition to in machine technological know-how and engineering, will locate this quantity a different and accomplished connection with a huge array of algorithms and architectures

Show description

Read or Download Algorithms and Architectures (Neural Network Systems Techniques and Applications) PDF

Best electrical & electronic engineering books

The MathML Handbook by Pavi Sandhu PDF

This consultant presents an summary of MathML and its sensible functions, explains easy suggestions equivalent to XML syntax, presentation markup, content material markup and mixed markup, and discusses using different server aspect purposes

MIMO Antenna Technology for Wireless Communications - download pdf or read online

This e-book assembles assurance on all elements of MIMO expertise besides updated info on key similar matters. participants from best educational and business associations around the globe proportion their services and lend the e-book a world viewpoint. They lead readers progressively from uncomplicated to extra complicated options, from propagation modeling and function research to space-time codes, a variety of structures, implementation recommendations and barriers, sensible process improvement concerns, box trials, and community making plans concerns.

Get Probability, random variables, and random signal principles PDF

This concise creation to likelihood concept contains at the luck of past variants, providing readers a logical, well-organized examine the elemental of the subject--includes functions that boost engineers' seize of likelihood recommendations. New! insurance of discrete-time random techniques and sequences, and different basic issues regarding electronic sign processing.

Get Analog Signal Processing PDF

Analog sign Processing brings jointly in a single position vital contributions and state of the art study leads to this speedily advancing region. Analog sign Processing serves as an exceptional reference, supplying perception into one of the most vital concerns within the box.

Additional info for Algorithms and Architectures (Neural Network Systems Techniques and Applications)

Sample text

As before, our task is to adjust the weights of the student RBF to find an estimating function fs that minimizes the average generalization error E(fs). The notion of a teacher network is not used; the task is described by a distribution VXXY over input space and output space, which defines the probability of the examples. We do require that E is bounded, so that the expectation always exists. Denoting the space of functions that can be represented by the student as Fs, we define opt(F5) as the infimum of E(fs) over Fs, so that the aim of learning is to find a function fs e Fs such that E(fs) is as near to opt(Fs) as possible.

Setting y = 0 eliminates the penalty and any consequences ridge regression might have. Figure 3 shows a number of fits to training sets similar to the one used in the previous subsection (see Fig. 2). The plotted curves are a small selection from a set of 1000 fits to 1000 training sets differing only in the choice of input points and the noise added to the output values. The radial basis function network which is performing the learning is also similar to that used previously except that a small amount of ridge regression, with a regularization parameter of y = 10~^^, has been incorporated.

B (see Fig. 2) with a very mildly regularized RBF network (y = 10~^^). Bias and variance are illustrated in the following example where we use ridge regression to control their trade-off. E, but basically it involves adding an extra term to the sum-squarederror which has the effect of penalizing high weight values. The penalty is controlled by the value of a single parameter y and affects the balance between bias and variance. Setting y = 0 eliminates the penalty and any consequences ridge regression might have.

Download PDF sample

Algorithms and Architectures (Neural Network Systems Techniques and Applications) by Cornelius T. Leondes


by Anthony
4.4

Rated 4.45 of 5 – based on 10 votes