Min-Hsuan Fan

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In this paper we use the tensor product notation as the framework of a programming methodology for designing various parallel prefix algorithms. In this methodology, we first express a computational problem in its matrix form. Next, we formulate a matrix equation for the matrix of the computational problem. Then, solve the matrix equation to obtain some(More)
This study aims to examine the fundamental forces driving stock returns and volatility across the international stock markets. Logistic regression analysis is used to investigate possible highly correlated among 9 international stock markets with stock market of Taiwan. Afterward, the highly correlated stock indices with Taiwan would be selected as the(More)
In this paper, we use the tensor product notation as the framework of a programming methodology for designing block recursive algorithms. We first express a computational problem in its matrix form. Next, we formulate a matrix equation for the matrix of the computational problem. Then, we try to find a solution of the matrix equation such that the solution(More)
The prediction of stock markets is an important and widely research issue since it could be had significant benefits and impacts, and the fuzzy time-series models have been often utilized to be the forecast models to make reasonably accurate predictions. For promoting the forecasting performance of fuzzy time-series models, this paper proposed a new model,(More)
The purpose of this research is to investigate the relation between international stock markets and Taiwan's stock market, and use the statistical method to identify international markets of high correlation with Taiwan's stock market as the input parameters of the ANFIS (Adaptive Network-based Fuzzy Inference System) model to improve the forecasting(More)
Matrix transposition is a simple, but an important computational problem. It explores many key issues on data locality. In this paper, we will design matrix transposition algorithms on various interconnection networks for VLSI circuit design, including omega, baseline and hypercube networks. Since different interconnection networks have their own(More)
In this paper, we use the tensor product notation as the framework of a programming methodology for designing block recursive algorithms on various computer networks. In our previous works, we propose a programming methodology for designing block recursive algorithms on sharedmemory and distributed-memory multiprocessors without considering the(More)
Abstract Many important computation problems can be specified by block recursive algorithms. For example, matrix transposition and fast Fourier transform are block recursive algorithms. In this paper, we present a methodology of VLSI circuit design for block recursive algorithms based on the tensor product theory. Matrix transposition and fast Fourier(More)