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Particle filter algorithm has a unique advantage in dealing with nonlinear, non-Gaussian state estimation. Particle filter method cannot accurately estimate the state of the system due to the particle degeneration and lack of particle diversity. In this paper, we propose a new particle filter algorithm called “Gauss based auxiliary particle filter” that introduces the real-time observation information...
This work seeks to improve upon the accuracy of birdsong analysis based species recognition. We intend to accomplish this by creating a more effective bird syllable segmentation algorithms (MIRS), Support Vector machine based classifiers are used to train the features of IRS and MIRS. The experimental results show the effectiveness of the proposed algorithm.
In order to improve fault forecasting model accuracy of back propagation neural network (BPNN), an improved prediction method of optimized BPNN based on Multilevel Genetic Algorithm (MGA) was proposed. We design new chromosome with multilevel structure, improve the encoding mode, fitness function and genetic operator. Which can optimizes the initial values of weights, thresholds and the structure...
Location based services are the hottest applications on mobile device nowadays. Indoor wireless position is the key technology to enable location based service to work well indoors, where Global Position System normally couldn't work. The main tendency of indoor wireless position is based on Bluetooth and RSSI (radio signal strength indicator). RSSI is the key parameter for wireless position. But...
In this paper a full chip implementation of a Mixed-signal hearing aid SoC is presented. The chip integrates Analog Front-End (AFE), Time-Division Multiplexed Power-On-Reset circuit (TDM-POR), Charge Pump (CP), Digital Signal Processing (DSP) platform and Class-D amplifier. Also, the Low-Dropout (LDO) voltage regulators and On-chip oscillator are both integrated to minimize the system overall size...
Link prediction in network attempts to predict the exist-yet-unknown links or future links in accordance with the node properties and the network typology. It has been used in many domains such as social network, biology experiment, and criminal investigations. Classical methods are based on graph topology structure and path features but few consider clustering information. Actually, clustering information...
In the research area of community detection which aims at detecting some highly cohesive vertex subsets in social network, there mainly exist some problems, such as the algorithms with comparatively excellent quality of the final partitioning usually have high time complexity and some other fast algorithms often result in low quality of partitioning or other disadvantages. Nowadays, the increasing...
In recent years? the study of social network is raising more and more attentions of researchers, locating the key nodes in social network is a hot research point. Lots of papers about how to discover the key nodes in social network such as mail network, micro log network was published. However, few people study on key nodes discovery in logistics network. In addition, most of methods of key nodes...
With the coming of the Big Data era, data mining has been confronted with new opportunities and challenges. Some limitations are exposed when traditional association rule mining algorithms are used to deal with large-scale data. In the Apriori algorithm, scanning the external storage repeatedly leads to high I/O load and brings about low performance. As for FP-Growth algorithm, the effectiveness is...
Image segmentation in the big data context is a hot topic in the field of image understanding. Contrary to traditional computing paradigm with precise description of problems, Granular Computing (GrC) is studied by utilizing the toleration of imprecise, incomplete, uncertain and mass information to make systems manageable, robust, low-cost and harmonious. Thus it is an efficient measure to simplify...
With the arrival of the big data era, information privacy and security issues become even more crucial. The Mining Associations with Secrecy Konstraints (MASK) algorithm and its improved versions were proposed as data mining approaches for privacy preserving association rules. The MASK algorithm only adopts a data perturbation strategy, which leads to a low privacy-preserving degree. Moreover, it...
Service-oriented situational data integration provides end-users an opportunity to integrate Internet-based data sources by composing data services, thereby satisfying users' immediate and personalized demands. Correlated query of multiple sources is a common way of data integration. Because it is difficult for users to select and compose services manually, an approach is proposed in this paper to...
Individual recognition is the technique which recognizes person's identity through his gait. Gait energy image (GEI) is a classical gait representation and it can be decomposed into structural part and detailed part. Then virtual gait energy image (VGEI) can be constructed in virtual space by integrating those two different parts. The generalized principal component analysis (GPCA) is applied to VGEI...
Bus trip is a healthy way to travel, and optimal bus dispatching decides social and economic benefits. Based on the analysis for both the existing traffic environment and bus dispatching, a mathematical model is proposed in this paper such that the goal function of this model are the average maximal satisfaction for passengers, the average loading rate of the maximum and the minimal average bus departure...
This paper proposes a hybrid particle swarm optimization algorithm for solving Job Shop Scheduling Problems (JSSP) to minimize the maximum makespan. A new hybrid heuristic, based on Particle Swarm Optimization (PSO), Tabu Search (TS) and Simulated Annealing (SA), is presented. PSO combines local search (by self-experience) with global search (by neighboring experience), achieving a high search efficiency...
This paper investigates the continuous-time distributed parameter estimation problem of sensor networks in uncertain sensing and communication environments. Each sensor uses a linear time-varying stochastic measurement model, and can only receive its neighbors' estimation states corrupted by stochastic noises. The random switches between different communication topologies are described by Markov processes...
This paper studies the adaptive tracking control for systems with quantized output observations and one unknown parameter. A projection algorithm is proposed for parameter identification, based on which an adaptive control law is designed via the certainty equivalence principle. By use of the conditional expectation of the quantized observation with respect to the estimates, it is shown that the identification...
Up to now, extensive research has been done on link failure recovery of optical multicast protection, but rarely for node failure recovery. To deal with the severe impact of node failures, we have recently developed two p-cycle based optical multicast protection approaches for 100% combined node and link failure recovery. This paper reviews our recent work on the p-cycle based multicast protection...
This paper studies on how to improve the efficiency of multilayer relationship checking, which was the most complex and time-consuming operation in land plan spatial data quality checking. The existing researches on spatial data quality mostly focused on how to evaluate spatial data quality, but few studies on efficiency. With an in depth study on the characteristics of multilayer relationship, we...
This paper proposes a knowledge retrieval model combining knowledge search with data mining technologies. In this model, data mining is integrated into the whole retrieval procedure of query optimizing, searching, results analyzing, and resources constructing. It realizes knowledge retrieval by various approaches, different levels, and multi-modes, and significantly improves knowledge retrieval level...
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