We propose a model for natural images in which the probability of an image is proportional to the product of the probabilities of some filter outputs. We encourage the system to find sparse features by using a Studentt distribution to model each filter output. If the t-distribution is used to model the combined outputs of sets of neurally adjacent filters, the system learns a topographic map in...

The invert transform approach can be useful in teaching subjects where convolutions are introduced or used, as in signals and systems courses. In this paper, we demonstrate that the approach can also simplify the presentation and implementation of the Wiener Filter when introduced to advanced undergraduate or entry level graduate students in statistical signal processing and Kalman filtering co...

The non-stationary Poisson noise in single photon emission computed tomography (SPECT) sinogram is a major cause to compromise the quality of reconstructed images and challenge any compensation strategy for photon attenuation, scatter and collimator response. Research utilizing threedimensional Wiener filter after Anscombe transformation, which converts Poisson distributed noise into Gaussian d...

Formulae connecting the multiple Stratonovich integrals with single Ogawa and Stratonovich integrals are derived. Multiple Riemann-Stieltjes integrals with respect to certain smooth approximations of the Wiener process are considered and it is shown that these integrals converge to multiple Stratonovich integrals as the approximation converges to the Wiener process.

This paper presents a two-dimensional Wiener model in spatial domain for a class of laser electrophotographic printers, and embeds it into a framework of model-based digital halftoning. The Wiener model comprises an FIR filter followed by a nonlinear static mapping. The nonlinear static mapping is synthesized using a fuzzy system to maximize its capability to approximate nonlinearity of high de...

In this paper we introduce the generalized feedforward filter, a new class of adaptive filters that combines attractive properties of finite impulse response (FIR) filters with some of the power of infinite impulse response (IIR) filters. A particular case, the gamma filter, generalizes Widrow’s adaptive transversal filter (adaline) to an infinite impulse response filter. Yet, the stability con...

The nonlinear speech signal decomposition based on Volterra-Wiener functional series is described. The nonlinear filter bank structure is proposed for phonemes recognition solving.