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Speech feature learning is very important for the design of classification algorithm of Parkinson's disease (PD). Existing speech feature learning method for classification of PD just pays attention to the speech feature. This paper proposed a novel hybrid feature learning algorithm which puts the features of all the speech segments of each subject together, thereby obtaining new and high efficient...
Factory inspections are a major issue facing factory management teams. Many parts of a factory require routine inspections, and many unexpected situations must be followed up. Furthermore, limitations in manpower and time make it impossible to conduct full inspections every day. In this study, we developed a system by which to map out routes for daily inspections using a skyline algorithm. Inspection...
There is an explosion in the number of new approaches being developed for extracting information from biological data, creating a need for intelligent ways to utilize so many methods. We take a perspective based on viewing methods as filters which reject undesired data and which may have complementary and redundant performance. We consider approaches for efficiently combining such filters. We provide...
For the problem of limited rule bases and inaccurate matching of Chinese Natural Language Processing (NLP), this paper presents a new NLP method based on Semantic Structure Tree (SST). Through establishing SST, this paper calculates the evaluation index to find out the most suitable semantic combination from all possible SST. In order to improve the semantic recognition recall and precision, this...
In original data, there may exist redundant features, irrelevant features, noisy features besides informative features. Extracting informative features while eliminating the others is the goal of feature selection. This paper proposed a new feature selection algorithm based on Relief algorithm and SVM-RFE algorithm, and it is strongly targeted to eliminate the unnecessary features. Finally, We test...
In this paper, parameter of ADRC for spacecraft attitude maneuvering is optimizated. Nonlinear dynamics model of spacecraft attitude describes attitude motion. Particle Swarm Optimization Algorithm is used for parameter optimization of ADRC. The controller index which describes attitude adjustment capacity of three axes is designed. The influence of controller parameter is quantifiable on the control...
In indoor environment, there are gross errors in random measured values of base station, which has effect on generalization ability of BP neural network and then results in low location accuracy. In order to improve location accuracy, location algorithm of BP Neural Network based on residual analysis is proposed, namely conducting pretreatment on measured values separately in training phase and location...
Pollard rho method and its parallelized variant are at present known as the best generic algorithms for computing elliptic curve discrete logarithms. We design new iteration functions for the parallel rho method by exploiting the fact that for any two points P and Q, we can efficiently get P-Q when we compute P+Q. We present a careful analysis of the alternative rho method with new iteration functions...
This paper mainly describes a search module, based on the BP neural network model, in Beijing Vocational College of Electronic Science Student Work Management System. The module is for selecting the appropriate work based on the machine learning. This module creates the BP model for every user and adjusts the weight and threshold of the BP model while students use the search module to browse other...
Although the problem of k-area coverage has been intensively investigated for dense wireless sensor networks (WSNs), how to arrive at a k-coverage sensor deployment that optimizes certain objectives in relatively sparse WSNs still faces both theoretical and practical difficulties. In this paper, we present a practical algorithm LAACAD (Load balancing k-Area Coverage through Autonomous Deployment)...
This paper put forward a repetitive control algorithm based on virtual resistance to the question that improving the gain characteristic of LCL filter circuit results in increased power lose. Apply the algorithm to embedded repetitive control system, and one new repetitive controller based on virtual resistance is formed, then use the controller to control the grid-connected part of PV system. Simulation...
Heze International Peony Fair develops the local economy, But subject to weather conditions, predicting peony florescence hardly meets the actual date. In order to accurate predicting, multiple linear regression analysis and multiple nonlinear regression analysis have been mentioned. The relationship of the factors which impact the peony florescence such as light, temperature and moisture, etc, is...
The energy consumption and the lifetime in wireless sensor network (WSN) can be investigated from the perspective of network topology division. A connected key nodes discovering algorithm based on loop detection between neighbor nodes was proposed in this paper. Moreover, we proposed the principle and theoretical analysis of this algorithm. This algorithm can be used to find the connected key nodes...
A key security level gradation method is proposed which is helpful to counter IEA (Iterative Encryption Attack) and provides RSA with favorable immunity against it. Firstly, we analyze the course of IEA in detail, and then present the concept of security grade of key-pair and the hierarchy of grades, and propose an algorithm that grades security grade of key-pairs. Secondly, we define the concept...
The classic TV(Total Variation)-L1 model for gray value image denoising is extended to a generalized TV-L1 model firstly, which is then extended to generalized MTV-L1 model for color image denoising based on MTV(Multichannel Total Variation) regularization. By introducing the concept of non-local MTV based on non-local means, the generalized non-local MTV-L1 model is designed for noise removal of...
Cluster analysis of gene expression data is one of the most useful tools for identifying biologically relevant groups of genes, however, gene expression data suffer severely from the problems of measurement noise, dimension curse, high redundancy between genes, and the functional annotation of genes is incomplete and imprecise. These properties lead to most of the traditional clustering algorithms...
We report on the development and implementation of a robust algorithm for extracting 2-Dim code Area in video images. The algorithm concludes two main steps, firstly, convert the RGB images into gray-scale images and location the point of max local radio in the gray image. These points are so-called corner points. Secondly we used the points to clustering and the results of the clustering can be used...
Cluster-based routing protocol is currently a hot research in wireless sensor network. In this paper, we propose an improved method RECHS(Redundant and Energy-efficient Clusterhead Selection) for LEACH protocol to balance network load and to extend the network life. In order to selecting reasonable clusterheads, our scheme first selects initial clusterheads and initial redundant clusterheads. By comparing...
In this paper we give an algorithm for computing a bidirectional minimal polynomial (a characteristic polynomial with not only minimal degree but also a nonzero constant term) of a given finite-length multisequence by modifying a lattice-based linear feedback shift register synthesis algorithm for multisequences. We also describe the set of all such polynomials for a multisequence.
Aiming at the overlapping phenomenon that exists among the cells in the actual mice macrophages image, this paper presents the method of image segmentation based on Otsu threshold and watershed of distance transform. The image is first segmented by Otsu threshold algorithm. Then erosion and dilation morphological operators are used to get rid of noises. Finally, the watershed algorithm based on distance...
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