14 research outputs found

    Direct Frequency-Domain Deconvolution when the Signals Have No Spectral Inverse

    No full text
    We describe a new method of frequency-domain deconvolution when the kernel has no spectral inverse. Discrete frequency interpolation is used to aviod zero-valued frequency samples. The algorithm does not suffer from the spectral singularities of the original kernel, its complexity is proportional to the fast Fourier transform, and a comparative noise study showed improved performance relative to the direct frequency-domain method. 1 Introduction When we are interested in characteristics of a system, it is very natural to observe the system operation referring to its output signal. Then, the characteristic behaviour is generally explained either by the impulse response in an input-output model or by the internal state changes in a state-space model. Nevertheless, to establish the backward connection from the system output to its characteristics or input signals, we face the inverse problem that is to be solved by a kind of deconvolution. Many different approaches to deconvolution have ..

    Complexity In Signal Processing Using Cepstral Approach

    No full text
    373, which is better as with another method suitable for the real-time cepstral processing, i.e. the adaptive phase integration, at the same complexity level. 1 Introduction In many applications, signals that are overlapped in time and have approximately the same frequency contents have to be separated. It means the problem of nonlinear filtering which, however, is transformed to a simple linear filter if the theory of generalized superposition [1] is applied. Generalized superposition is based on homomorphic systems [2] consisting of an input characteristic system that converts a nonlinear operation to a linear one, e.g. convolution to addition, a linear system, and an output inverse characteristic system. Denote by x(n), h(n), and y(n) a system input, unit-sample response, and output signal, respectively. Let y(n) be a convolution<F
    corecore