Recent Submissions

  • Recognition of Epileptiform Patterns in the Human Electroencephalogram Using Multi-Layer Perceptron 

    Magdolen, J.; Zidek, F.; Mokran, V. (Společnost pro radioelektronické inženýrství, 1995-06)
    Automatic detection of epileptiform patterns is highly desirable during continuous monitoring of patients with epilepsy. This paper describes an unconvential system for automatic off-line recognition of epileptic sharp ...
  • Analysis of Spread Spectrum System Parameters for Design of Hidden Transmission 

    Luc, A. (Společnost pro radioelektronické inženýrství, 1995-06)
    A short analysis of spread spectrum communication system is performed with respect to the determination of its fundamental system parameters for transmitted signal hidden in the noise. The paper shows dependence of processing ...
  • Transfer Functions and Chain Parameters of SC Equivalents 

    Divis, L.; Bicak, J. (Společnost pro radioelektronické inženýrství, 1995-06)
    When designing SC filters, the question of charge transfer functions and chain parameters becomes very interesting. A complete analysis of this question based on standard charge conservation equations and their solution ...
  • Active Two-Port Equivalent Noise Parameters 

    Hruskovic, M.; Hribik, J.; Kostal, M.; Groschl, M.; Benes, E. (Společnost pro radioelektronické inženýrství, 1995-06)
    A method of the calculation of active two-port equivalent noise parameters from n measured noise figures for different values of signal source output admittance is given.
  • Generalized Frequency Domain LMS Adaptive Filter 

    Dohnal, F. (Společnost pro radioelektronické inženýrství, 1995-06)
    The most significant problems of acoustic echo canceller (AEC) realizations are high computational complexity and insufficient convergence rate of the applied adaptive algorithms. From the analysis of the frequency domain ...
  • Learning the Neural Networks by the Set of Patterns Having the Form of Fuzzy Data 

    Mikula, V. (Společnost pro radioelektronické inženýrství, 1995-06)
    This paper deals with the possibility of learning the neural networks by the use of training patterns having the form of both the crisp numerical data as well as fuzzy numbers.