By Topic

Artificial Neural Networks, 1991., Second International Conference on

Date 18-20 Nov. 1991

Filter Results

Displaying Results 1 - 25 of 82
  • Homotopy continuation method for neural networks

    Publication Year: 1991, Page(s):19 - 23
    IEEE is not the copyright holder of this material | Click to expandAbstract | PDF file iconPDF (234 KB)

    This paper proposes the use of homotopy continuation method for training the neural networks. Homotopy methods have been demonstrated to be superior to gradient descent methods in many applications such as nonlinear optimization problems, mathematical analysis, and more recently, signal processing. The power of these methods lies in their ability to provide globally convergent solutions, and under... View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Operational fault tolerance of the ADAM neural network system

    Publication Year: 1991, Page(s):285 - 289
    IEEE is not the copyright holder of this material | Click to expandAbstract | PDF file iconPDF (469 KB)

    Neural networks offer a powerful parallel distributed computational system which can be trained to solve many problems. They also appear to be inherently fault tolerant. This is unlike a conventional computing system where fault tolerance is achieved by redundancy, thus increasing its overall complexity. The fault tolerance of the advanced distributed associative memory neural network (ADAM) is in... View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • A frame based implementation architecture for neural networks

    Publication Year: 1991, Page(s):54 - 58
    IEEE is not the copyright holder of this material | Click to expandAbstract | PDF file iconPDF (244 KB)

    Neural networks have the potential to provide very cost effective pattern recognition machines provided that suitable hardware implementations can be found. The applicability of common neural network structures, such as the multi-layer feed-forward network, to different pattern recognition problems means that any particular implementation scheme will be widely applicable. This generality makes it ... View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • A high order feedback net (HOFNET) with variable non-linearity

    Publication Year: 1991, Page(s):59 - 63
    IEEE is not the copyright holder of this material | Click to expandAbstract | PDF file iconPDF (196 KB)

    Most neural networks proposed for pattern recognition sample the incoming image at one instant and then analyse it. This means that the data to be analysed is limited to that containing the noise present at one instant. Time independent noise is therefore, captured but only one sample of time dependent noise is included in the analysis. If however, the incoming image is sampled at several instants... View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • A fast, novel, cascadable design for multi-layer networks

    Publication Year: 1991, Page(s):64 - 68
    IEEE is not the copyright holder of this material | Click to expandAbstract | PDF file iconPDF (232 KB)

    It is now well established that multi-layer neural networks can achieve results in pattern recognition problems which are comparable to, if not slightly better than, the results obtained with the best conventional algorithms available. The authors argue that if analogue VLSI technology is to represent a real alternative to digital implementations of these multilayer networks, it must not only deli... View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Nonlinear time series prediction

    Publication Year: 1991, Page(s):354 - 358
    IEEE is not the copyright holder of this material | Click to expandAbstract | PDF file iconPDF (196 KB)

    There is considerable interest in the use of nonlinear techniques to perform prediction of naturally occurring time series, e.g. medical signals and signals from seismic returns. The motivation in considering these techniques lies in the fact that may of the underlying generation mechanisms are nonlinear. There has been growing interest in the use of neural network architectures for such applicati... View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Further developments of a neural network speech fundamental period estimation algorithm

    Publication Year: 1991, Page(s):340 - 344
    IEEE is not the copyright holder of this material | Click to expandAbstract | PDF file iconPDF (300 KB)

    This work describes a speech fundamental period estimation algorithm that estimates the time of excitation of the vocal tract using a pattern classifier, the multi-layer perceptron (MLP). The pattern classifier was trained using speech semi-automatically labelled by means of an algorithm that makes use of the output from a Laryngograph. Various issues arising in the training of the system were exp... View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Logical neural nets and distributed implementations of weighted regular languages

    Publication Year: 1991, Page(s):158 - 162
    IEEE is not the copyright holder of this material | Click to expandAbstract | PDF file iconPDF (296 KB)

    A logical neural network, Aleksander (1), is a finite state machine then it is only possible to recognise regular grammars with these networks. When extra memory is associated with the nodes of these networks, the computational power of the model is increased and now weighted regular grammars, Salomaa (14), can be recognised. Through a constructive method based on the complexity of the production ... View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Segmentation and recognition of calligraphic text

    Publication Year: 1991, Page(s):214 - 218
    IEEE is not the copyright holder of this material | Click to expandAbstract | PDF file iconPDF (340 KB)

    Calligraphic Hebrew text was scanned using a conventional scanner yielding a facsimile type of image. This image was aligned into lines of symbols by taking pixel density histograms in many directions. Separation of overlapping lines and symbols was made using an edge detecting borderline follower technique. After finding and circumscribing the first symbol, a search was made for expected nearby i... View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Adaptive equalization using the lp back propagation algorithm

    Publication Year: 1991, Page(s):10 - 13
    IEEE is not the copyright holder of this material | Click to expandAbstract | PDF file iconPDF (164 KB)

    This paper discusses the performance of adaptive equalization using lp, 1<p⩽2, back propagation algorithm. The results indicate that as p decreases, the convergence time tends to reduce roughly linearly. Considerable improvement in the rate of convergence and bit error rate performance for 1<p<2 over p=2, has been shown to be fea... View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • A statistical investigation of cost-function derivatives for neural networks with continuous activation functions

    Publication Year: 1991, Page(s):34 - 38
    IEEE is not the copyright holder of this material | Click to expandAbstract | PDF file iconPDF (256 KB)

    By making simple assumptions on the distribution of potentials at the nodes of a feed-forward multilayer network with continuous activation functions the author derives analytic expressions for the mean and standard deviation of the values of the cost function and root-mean-square values of its derivatives. He shows how this information can be used to obtain systematic estimates of the range of we... View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • A general purpose neural network architecture for time series prediction

    Publication Year: 1991, Page(s):323 - 327
    IEEE is not the copyright holder of this material | Click to expandAbstract | PDF file iconPDF (236 KB)

    The paper describes an innovative neural network architecture which is particularly suited to time series prediction applications. The system, which based on a fully connected recurrent network, has been evaluated for both deterministically and stochastically generated time series as well as real process data. Results are presented for the latter and comparisons made against performance achieved b... View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Multicriterion neural network optimization approach to image reconstruction from projections

    Publication Year: 1991, Page(s):103 - 106
    IEEE is not the copyright holder of this material | Click to expandAbstract | PDF file iconPDF (204 KB)

    A multicriterion optimization based neural model with application to image reconstruction from projections is proposed. The reconstruction procedure consists of two stages: estimation of the parameters of the neural network model and image reconstruction. Computer simulation results showed that the novel method is very efficient View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Seismic wavelet extraction using artificial neural networks

    Publication Year: 1991, Page(s):95 - 99
    IEEE is not the copyright holder of this material | Click to expandAbstract | PDF file iconPDF (336 KB)

    Geophysical events are of interest to the interpreter as an indicator of geological boundaries and structures. In structural analysis, extraction of reflection events is still commonly done by hand, a process which is error-prone and time consuming. Attempts to automate the process are hindered by the absence of a clear, robust and universal picking algorithm. A new feature extraction technique fo... View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Error recovery behaviour of feedback RAM-networks

    Publication Year: 1991, Page(s):304 - 308
    Cited by:  Papers (1)
    IEEE is not the copyright holder of this material | Click to expandAbstract | PDF file iconPDF (252 KB)

    Presents an analysis of the dynamics involved in the process of error recovery in Boolean neural nets with feedback loops. The main objective of the work is to show the conditions under which a randomly generated RAM-network recovers from input and state errors. RAM-nets of the type mentioned tend to have some inherent stability with respect to its input sequence. The approach adopted here is a pr... View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • A rule-based dynamic back-propagation (DBP) network

    Publication Year: 1991, Page(s):170 - 174
    IEEE is not the copyright holder of this material | Click to expandAbstract | PDF file iconPDF (292 KB)

    The paper presents and explains experiments performed on a neural network paradigm which works on the Back-Propagation (BP) formula together with additional rules for modifying the net structure. The function of the rules is to control the number of hidden units and their interconnections of a BP net. Hence, the net is capable of `evolving' into the optimal topology itself without interference fro... View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Automatic signalized point recognition with feed-forward neural network

    Publication Year: 1991, Page(s):359 - 363
    IEEE is not the copyright holder of this material | Click to expandAbstract | PDF file iconPDF (500 KB)

    The recognition and accurate location of specific patterns, such as of special targets or signalized points in digital images, is an important step in photogrammetric measurement procedures. This paper explores the capability of the feed-forward neural network using a version of back-propagation training for the recognition of targets that appear in digitized images of aerial photographs. These ta... View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • A probabilistic rule-based system in artificial neural networks

    Publication Year: 1991, Page(s):153 - 157
    IEEE is not the copyright holder of this material | Click to expandAbstract | PDF file iconPDF (296 KB)

    The authors propose a hybrid system in which a probabilistic rule-based system is implemented as a forward chaining inference machine. Based upon this design, the rule-based system could be equipped with a generalization function, automatic rule learning functions and a damage tolerant feature. The system contains three networks, Hopfield binary neural network, a single-layered feedforward neural ... View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • An analysis of self-organising networks based on goal-seeking neurons

    Publication Year: 1991, Page(s):257 - 261
    IEEE is not the copyright holder of this material | Click to expandAbstract | PDF file iconPDF (272 KB)

    The principle involved in applying self-organising architectures to pattern recognition problems is that patterns which share common features are clustered together, with each cluster representing one and only one class. One architecture that follows such a principle is the GSN self-organising architecture (GSN8) a Boolean neural network proposed by Filho, Fairhurst and Bisset (1990, 19... View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Normalised hierarchical data structures for automatic target recognition

    Publication Year: 1991, Page(s):229 - 233
    IEEE is not the copyright holder of this material | Click to expandAbstract | PDF file iconPDF (320 KB)

    A new method is presented that involves teaching an artificial neural network (advanced distributed associative memory ADAM) with a number of synthetic images resulting from a hierarchical data structure descriptor that characterises an object's 3D volume. The method results in a highly accurate recognition process that significantly reduces the duration of a generally time consuming training proc... View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Isolated word recognition with the radial basis function classifier

    Publication Year: 1991, Page(s):345 - 349
    IEEE is not the copyright holder of this material | Click to expandAbstract | PDF file iconPDF (288 KB)

    The paper introduces a method of optimising the radial basis function classifier representing a compromise between fast heuristic approaches and a fully adaptive approach. The method is especially suitable when the size and complexity of the classification problem are such that large numbers of kernel functions are required to maximise generalisation (minimise error rate on test data). The problem... View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Optimization and training of feedforward neural networks by genetic algorithms

    Publication Year: 1991, Page(s):39 - 43
    Cited by:  Papers (5)
    IEEE is not the copyright holder of this material | Click to expandAbstract | PDF file iconPDF (356 KB)

    The training of feedforward neural networks by backpropagation requires much time-consuming experimentation by the network designer. The authors use the genetic algorithm formalism to optimize network structure and training parameters automatically, so as to allow successful back-propagation learning. Additionally, they describe a method to optimize network weights directly using the genetic algor... View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Second International Conference on Artificial Neural Networks (Conf. Publ. No.349)

    Publication Year: 1991
    IEEE is not the copyright holder of this material | Click to expandAbstract | PDF file iconPDF (24 KB)

    The following topics were dealt with: artificial neural networks theory; implementations; images; engineering applications; dynamical systems; control and robotics; hybrids; speech and natural language; medical applications; and character recognition View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • EEG analysis using self-organisation

    Publication Year: 1991, Page(s):210 - 213
    Cited by:  Papers (1)
    IEEE is not the copyright holder of this material | Click to expandAbstract | PDF file iconPDF (216 KB)

    The electro-encephalogram (EEG) has formed the basis for the classification of sleep into several stages. The authors propose a method of sleep analysis which requires no pre-defined application of rules, and aims to give some indication of the dynamics of sleep in humans. The authors show that the use of a self-organising feature map has enabled clustering of feature vectors in a high dimensional... View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Neural classification of chest pain symptoms: a comparative study

    Publication Year: 1991, Page(s):200 - 204
    IEEE is not the copyright holder of this material | Click to expandAbstract | PDF file iconPDF (320 KB)

    The authors demonstrate the effectiveness of neural networks in the diagnosis of heart attacks (acute myocardial infarction). Two neural network classifiers are compared. The multi-layered Perceptron is found to perform well but the probabilistic interpretation of its output is not well defined. The Boltzmann Perceptron Classifier is found to have comparable performance and has the advantage that ... View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.