Psychometric function plots the percentage of the correct responses among an entire pool of responses (cumulative probability) in a psychophysical task versus the amount of change in an independent variable. These changes in the independent variable are made with reference to a constant initial value. If this initial value is altered, the psychometric function will change according to Weber’s l...

Psychometric function plots the percentage of the correct responses among an entire pool of responses (cumulative probability) in a psychophysical task versus the amount of change in an independent variable. These changes in the independent variable are made with reference to a constant initial value. If this initial value is altered, the psychometric function will change according to Weber’s l...

The existence of fixed point in orthogonal metric spaces has been initiated by Eshaghi and et. al [7]. In this paper, we prove existence and uniqueness theorem of fixed point for mappings on $varepsilon$-connected orthogonal metric space. As a consequence of this, we obtain the existence and uniqueness of fixed point for analytic function of one complex variable. The paper concludes with some i...

We give a simple proof of classical theorem by A. Máté, P. Nevai, and V. Totik on asymptotic behavior orthogonal polynomials the unit circle. It is based new real-variable approach involving an entropy estimate for orthogonality measure. Our second result extension G. Freud averaged convergence Fourier series. also discuss some related open problems in theory

The main purpose of this research is to extend some fixed point results in orthogonal metric spaces. For this purpose, first, we investigate new mappings in this spaces. We introduce the new notions of functions. Then by using it, we define contractive mappings and then we establish and prove some fixed point theorems for such mappings in orthogonal metric spaces. Then by utilizing examples of ...

In this paper, we develop the theory of the wavelet transform over Galois elds. To avoid the limitations inherent in the number theoretic Fourier transform over nite elds, our wavelet transform relies on a basis decomposition in the time domain rather than in the frequency domain. First, we characterize the in nite dimensional vector spaces for which an orthonormal basis expansion of any sequen...