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Digitally programmable nonlinear function generator for neural networks

Digitally programmable nonlinear function generator for neural networks

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The design of a new digitally programmable analogue circuit well suited for the implementation of several sets of nonlinear functions by approximating them by using a linear combination of sigmoidal terms is presented. The proposed circuit, allowing the building of several collections of nonlinear functions, would be useful in modelling artificial neural networks, fuzzy as well as partial differential equations based circuits.

References

    1. 1)
    2. 2)
      • G. Cybenko . Approximation by superposition of a sigmoidal function. Math. Control Signals Syst. , 303 - 314
    3. 3)
      • A. Kaufmann , M.M. Gupta . (1985) Introduction to fuzzy arithmetic: theory and applications.
    4. 4)
      • J.D. Dimitrov . A Bell-shape pulse generator. IEEE Trans. Instrum. Meas. , 4 , 667 - 670
    5. 5)
      • J.S. Walker , S.G. Krantz . (1999) A primer on wavelets and their scientific applications.
    6. 6)
      • R. FitzHugh . Impulses and physiological states in theoretical models of nerve membrane. Biophys. J. , 445 - 466
    7. 7)
      • J. Nagumo . An active pulse transmission line simulating nerve axons. Proc. IRE , 2061 - 2070
    8. 8)
      • J. Hertz . (1991) Introduction to the theory of neural computation.
    9. 9)
      • Special issue on cellular neural networks. IEEE Trans. Circuits Syst. , 3
    10. 10)
    11. 11)
      • Delgado-Restituto, M.: `Current-mode piecewise-linear function generator', Proc. IEEE Int. Symp. on Circuits and Systems, ISCAS'96, May 1996, 1, p. 469–472.
    12. 12)
      • F. Sargeni , V. Bonaiuto . Programmable CNN analogue chip for RD-PDE multi-method simulations programmable CNN analogue chip for RD-PDE multi-method simulations, Analog integrated circuits and signal processing.
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