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The optimization of a model that expresses time series data for a given period is a problem associated with the development of a regression model that estimates future data on the extension of the past data time series. This is a two-step optimization problem where the order of past data used in the regression model (number of orders of the solution space) is decided, and weighted coefficients for...
Recently, there has been a growing demand for the design principle of assisting system. This paper presents a new framework of the assisting system design based on a continuous/discrete hybrid system model of the driving behavior and the model predictive control scheme. First of all, the driving behavior is identified as the piecewise ARX model, then it is explicitly embedded in the optimization problem...
This paper presents a new troubleshooting methodology for 3G Long Term Evolution (LTE) networks based on a closed-form expression between Radio Resource Management (RRM) and Key Performance Indicator (KPI) parameters, using statistical learning. This methodology aims at locally optimising the RRM parameters of the cells with poor performance in an iterative manner. The optimization engine uses the...
Personal digital assistant (PDA) is more and more popular due to its powerful functions. To protect the personal information of PDA, we adopt the technology of text-independent speaker verification (SV) for this kind of embedded system. In this paper, Gaussian mixture model (GMM) and universal background model (UBM) are addressed in detail. The optimization of mathematical computation of GMM-UBM guarantees...
In this paper, we address the problem of orthogonal frequency-division multiplexing (OFDM) channel estimation in the presence of phase noise (PHN) and carrier frequency offset (CFO). In OFDM systems, PHN and CFO cause two effects: the common phase error (CPE) and the intercarrier interference (ICI) which severely degrade the accuracy of the channel estimate. In literature, several algorithms have...
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