The monitor system architecture in ternary optical computer (TOC) was discussed. There were some important modules, such as the client, network communication module (NCM), data preprocess module (DPM), operation-request scheduling module (ORSM), optical processor allocation module (OPAM) and the embedded system in the architecture. And the communication protocols between these modules were analyzed and designed. At the same time, the functions of the modules were introduced.
The purpose of this study is to explore the allocation of lots of data-bit resource in a ternary optical computer (TOC). It analyzes previous important results and proposes the Dynamic Data-bit Allocation (DDBA) method. And it divides 1024 data-bits of TOC into 8 sizes of suanweis by using static grouping technology, and discusses the process of DDBA in detail. Finally, an example is given to illustrate the allocation process.
Removing noise from the original image plays an important role in many important applications involving image-based medical diagnosis and visual material examination for public security, and so on. Among them, there have been several published methods to solve the related problem, however, each approach has its advantages, and limitations. This paper examines a new measure of denosing in space domain based on 2-D kernel regression which overcomes the difficulties found in other measures. The idea of this method mainly let the values of a row or a column from an image are taken as the measured results of a fitting function. The following step is to estimate the weight coefficients using least square method. Finally, we obtain an denoised image by resampling the estimated function, and the variable x denotes the coordinate of an image. Results of an experimental applications of this method analysis procedure are given to illustrate the proposed technique, and compared with the basic wavelet-thresholding algorithm for image denoising.
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