A general method for sensor linearization based on neural networks

The purpose of this work is to investigate the properties of spreading speeds for the monotone semiflows. According to the fundamental work of Liang and Zhao [(2007) Comm. Pure Appl. Math.60, 1–40], the spreading speeds of the monotone semiflows can be derived via the principal eigenvalue of linear operators relating to the semiflows. In this paper, we establish a general method to analyse the sign and the continuity of the spreading speeds. Then we consider a limiting case that admits no spreading phenomenon. The results can be applied to the model of cellular neural networks (CNNs). In this model, we find the rule which determines the propagating phenomenon by parameters.

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Global Stability and Bifurcation in Delayed Bidirectional Associative Memory Neural Networks With an Arbitrary Number of Neurons

Journal of Dynamic Systems Measurement and Control ◽

10.1115/1.4036229 ◽

2017 ◽

Vol 139 (8) ◽

Cited By ~ 3

Author(s):

Elham Javidmanesh

Keyword(s):

Neural Network ◽

Neural Networks ◽

Hopf Bifurcation ◽

Global Stability ◽

Associative Memory ◽

Bam Neural Networks ◽

Bidirectional Associative Memory ◽

Numerical Examples ◽

Bam Neural Network ◽

General Method

In this paper, delayed bidirectional associative memory (BAM) neural networks, which consist of one neuron in the X-layer and other neurons in the Y-layer, will be studied. Hopf bifurcation analysis of these systems will be discussed by proposing a general method. In fact, a general n-neuron BAM neural network model is considered, and the associated characteristic equation is studied by classification according to n. Here, n can be chosen arbitrarily. Moreover, we find an appropriate Lyapunov function that under a hypothesis, results in global stability. Numerical examples are also presented.

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Sensor linearization with neural networks

IEEE Transactions on Industrial Electronics ◽

10.1109/41.969414 ◽

2001 ◽

Vol 48 (6) ◽

pp. 1288-1290 ◽

Cited By ~ 33

Author(s):

N.J. Medrano-Marques ◽

B. Martin-del-Brio

Keyword(s):

Neural Networks ◽

Sensor Linearization

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The Upstart Algorithm: A Method for Constructing and Training Feedforward Neural Networks

Neural Computation ◽

10.1162/neco.1990.2.2.198 ◽

1990 ◽

Vol 2 (2) ◽

pp. 198-209 ◽

Cited By ~ 340

Author(s):

Marcus Frean

Keyword(s):

Neural Networks ◽

Feedforward Neural Networks ◽

Multilayer Perceptrons ◽

Training Set ◽

Binary Variables ◽

Perceptron Algorithm ◽

Linear Threshold ◽

Recursive Rule ◽

And Training ◽

General Method

A general method for building and training multilayer perceptrons composed of linear threshold units is proposed. A simple recursive rule is used to build the structure of the network by adding units as they are needed, while a modified perceptron algorithm is used to learn the connection strengths. Convergence to zero errors is guaranteed for any boolean classification on patterns of binary variables. Simulations suggest that this method is efficient in terms of the numbers of units constructed, and the networks it builds can generalize over patterns not in the training set.

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A General Method for Spectrometer Design in the Scoff Approximation

Proceedings, annual meeting, Electron Microscopy Society of America ◽

10.1017/s0424820100092657 ◽

1976 ◽

Vol 34 ◽

pp. 538-539

Author(s):

J. R. Fields

Keyword(s):

Electron Microscope ◽

Transmission Electron Microscope ◽

Energy Analysis ◽

Incident Beam ◽

Scanning Transmission Electron Microscope ◽

Chemical Identification ◽

Scanning Transmission Electron ◽

Transmission Electron ◽

Scanning Transmission ◽

General Method

The energy analysis of electrons scattered by a specimen in a scanning transmission electron microscope can improve contrast as well as aid in chemical identification. In so far as energy analysis is useful, one would like to be able to design a spectrometer which is tailored to his particular needs. In our own case, we require a spectrometer which will accept a parallel incident beam and which will focus the electrons in both the median and perpendicular planes. In addition, since we intend to follow the spectrometer by a detector array rather than a single energy selecting slit, we need as great a dispersion as possible. Therefore, we would like to follow our spectrometer by a magnifying lens. Consequently, the line along which electrons of varying energy are dispersed must be normal to the direction of the central ray at the spectrometer exit.

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Phase behavior of cationic and anionic surfactants at low concentrations

Proceedings, annual meeting, Electron Microscopy Society of America ◽

10.1017/s0424820100123878 ◽

1992 ◽

Vol 50 (1) ◽

pp. 694-695

Author(s):

E. Naranjo

Keyword(s):

Phase Behavior ◽

Structural Characterization ◽

Dynamic Systems ◽

Anionic Surfactants ◽

Intermolecular Forces ◽

Stable Form ◽

Surfactant Mixtures ◽

Low Concentrations ◽

Cationic And Anionic Surfactants ◽

General Method

Equilibrium vesicles, those which are the stable form of aggregation and form spontaneously on mixing surfactant with water, have never been demonstrated in single component bilayers and only rarely in lipid or surfactant mixtures. Designing a simple and general method for producing spontaneous and stable vesicles depends on a better understanding of the thermodynamics of aggregation, the interplay of intermolecular forces in surfactants, and an efficient way of doing structural characterization in dynamic systems.

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