Parallel processing for digital picture comparison

In picture processing an important problem is to identify two digital pictures of the same scene taken under different lighting conditions. This kind of problem can be found in remote sensing, satellite signal processing and the related areas. The identification can be done by transforming the gray levels so that the gray level histograms of the two pictures are closely matched. The transformation problem can be solved by using the packing method. Researchers propose a VLSI architecture consisting of m x n processing elements with extensive parallel and pipelining computation capabilities to speed up the transformation with the time complexity 0(max(m,n)), where m and n are the numbers of the gray levels of the input picture and the reference picture respectively. If using uniprocessor and a dynamic programming algorithm, the time complexity will be 0(m(3)xn). The algorithm partition problem, as an important issue in VLSI design, is discussed. Verification of the proposed architecture is also given

Sampling expansions associated with quaternion difference equations

Starting with a quaternion difference equation with boundary conditions, a parameterized sequence which is complete in finite dimensional quaternion Hilbert space is derived. By employing the parameterized sequence as the kernel of discrete transform, we form a quaternion function space whose elements have sampling expansions. Moreover, through formulating boundary-value problems, we make a connection between a class of tridiagonal quaternion matrices and polynomials with quaternion coefficients. We show that for a tridiagonal symmetric quaternion matrix, one can always associate a quaternion characteristic polynomial whose roots are eigenvalues of the matrix. Several examples are given to illustrate the results

Enhanced Fuzzy Sliding Mode Control to MotionController of Linear Induction Motor Drives

[[abstract]]In this paper, an enhanced fuzzy sliding mode control system (EFSMC) is proposed for a linear induction motor (LIM) to achieve the position tracking. First, the dynamic model of LIM is investigated for considering the end effect and the friction force into the observer-based compensation design to cope with the time-varying uncertainties. Then, a sliding mode control (SMC) based on the backstepping control technique is presented with the combination of two fuzzy logic controllers. The first fuzzy logic controller is proposed, through a dynamic tune of the sliding surface slope constant of the SMC according to the controlled system states by a fuzzy logic unit. To relax the need of the upper bound of the lumped uncertainties in the SMC, the second fuzzy logic controller is presented, in which the upper bound of the lumped uncertainties can be estimated by a fuzzy inference mechanism. Finally, the experiments for several scenarios are conducted to demonstrate the effectiveness and robustness of the designed controller.[[conferencetype]]國際[[conferencedate]]20140711~20140713[[booktype]]電子版[[iscallforpapers]]

Monogenic Signal Associated with Linear Canonical Transform and Application to Edge Detection Problems

Monogenic signal is regarded as a generalization of analytic signal from the one dimensional space to the high dimensional space. It is defined by an original signal with the combination of Riesz transform. Then it provides the signal features representation, such as the local attenuation and the local phase vector. The main objective of this study is to analyze the local phase vector and the local attenuation in the high dimensional spaces. The differential phase congruency is applied for the edge detection problems.Comment: 11 pages, 2 figure