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检索条件"主题词=detection algorithms"

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Isolated Digit Speech Recognition in Malay Language Using Neuro-Fuzzy Approach

Isolated Digit Speech Recognition in Malay Language Using Ne...

引用

Asia International Conference on Modeling & Simulation

作者： Reem Sabah Raja N. Ainon Faculty of Computer Science and Information Technology University of Malaya Kuala Lumpur Malaysia

ISBN: (纸本)9781424441549

In this paper we discuss the development and implementation of an automated speaker-independent isolated Malay digit speech recognition system. The system is developed using Neuro-Fuzzy approach that combines the human-like reasoning style of fuzzy systems and the learning and connectionist structure of neural networks. To recognize the Malay speech digits, the endpoint detection algorithm is used to trim the silent duration in speech sample, the Mel Frequency Cepstral Coefficient technique is used to extract speech features, the subtractive clustering algorithm is applied to identify the fuzzy inference system, and the Adaptive Neuro Fuzzy Inference System (ANFIS) is used as a modern classification technique to train in identifying the features of speech. The performance of the system was evaluated by using 630 speech samples for training and testing, and experimental results showed that an overall 85.24% recognition rate was achieved.

关键词： Speech recognition Natural languages Fuzzy systems Neural networks Automatic speech recognition detection algorithms Mel frequency cepstral coefficient Feature extraction Clustering algorithms Inference algorithms

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Shape-adaptivewavelet encoding of depth maps

Shape-adaptivewavelet encoding of depth maps

引用

Picture Coding Symposium, PCS

作者： Matthieu Maitre Minh N. Do Microsoft Windows Experience Group Redmond USA Department of Electrical and Computer Engineering University of Illinois Urbana-Champaign USA

We present a novel depth-map codec aimed at free-viewpoint 3DTV. The proposed codec relies on a shape-adaptive wavelet transform and an explicit representation of the locations of major depth edges. Unlike classical wavelet transforms, the shape-adaptive transform generates small wavelet coefficients along depth edges, which greatly reduces the data entropy. The wavelet transform is implemented by shape-adaptive lifting, which enables fast computations and perfect reconstruction. We also develop a novel rate-constrained edge detection algorithm, which integrates the idea of significance bitplanes into the Canny edge detector. Along with a simple chain code, it provides an efficient way to extract and encode edges. Experimental results on synthetic and real data confirm the effectiveness of the proposed algorithm, with PSNR gains of 5 dB and more over the Middlebury dataset.

关键词： Encoding Wavelet transforms Codecs Wavelet coefficients Entropy detection algorithms Detectors Data mining PSNR Gain

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Hybrid anti-islanding algorithm for utility interconnection of distributed generation

Hybrid anti-islanding algorithm for utility interconnection ...

引用

International Conference for Technical Postgraduates (TECHPOS)

作者： Maher G. M. Abdolrasol Saad Mekhilef Department of Electrical Engineering University of Malaya Kuala Lumpur Malaysia

ISBN: (纸本)9781424452231

In this paper hybrid anti-islanding algorithm for utility interconnection of distributed generation is proposed. This algorithm is based on two detection schemes; namely active and passive. Active detection algorithm generates disturbances at the output by positive feedback and continuous feedback signal injection which is based on DQ implementation. On the other hand passive detection algorithm detects islanding by measuring voltage, frequency, active and reactive power. Using total harmonic distortion (THD) as an additional parameter is proposed in this paper. Passive detection algorithm uses several types of loads such as resistive, capacitive and inductive connected in parallel and compares the performance of the algorithm in each case.

关键词： Distributed control detection algorithms Output feedback Signal generators Distortion measurement Power measurement Voltage measurement Frequency measurement Reactive power Total harmonic distortion

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Novel QRM-MLD algorithm for V-BLAST systems with permuted channel matrix

Novel QRM-MLD algorithm for V-BLAST systems with permuted ch...

引用

IEEE International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC)

作者： Kai Wu Ling Sang Cong Xiong Xin Zhang Dacheng Yang Wireless Theories and Technologies Lab (WT&T) Beijing University of Posts and Telecommunications Beijing China

ISBN: (纸本)9781424451227

The maximum likelihood detection with QR decomposition and M-algorithm (QRM-MLD) has been proposed as a near-optimal multiple-input multiple-output (MIMO) detection scheme which can achieve near maximum likelihood (ML) performance with complexity greatly reduced. However, the performance of the QRM-MLD algorithm will deteriorate with the increasing of the number of transmit antennas, as well as the decreasing of the number of the selected nodes in each stage due to the abandoning of some hypotheses in each step of the tree search. To solve this problem, we modify the QR decomposition method through rearranging the channel columns based on the post-detection signal-to-noise ratio (SNR), which makes the process of the abandoning more reliable. Simulation results show that the new proposed algorithms achieve better performance compared with the conventional QRM-MLD algorithm, especially when the number of transmit antennas is large. Additionally, the increase of the complexity is negligible compared with that of the conventional QRM-MLD algorithm.

关键词： Transmitting antennas Receiving antennas Maximum likelihood detection Maximum likelihood decoding MIMO Power system reliability detection algorithms Computational complexity Performance loss Matrix decomposition

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Detecting dynamic communities in opportunistic networks

Detecting dynamic communities in opportunistic networks

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International Conference on Ubiquitous and Future Networks, ICUFN

作者： Kuang Xu Guang-Hua Yang Victor O.K. Li Shu-Yan Chan University of Hong Kong Hong Kong China University of Cambridge UK

In opportunistic networks, communities of mobile entities may be utilized to improve the efficiency of message forwarding. However, identifying communities that are dynamically changing in mobile environment is non-trivial. Based on random walk on graphs, in this paper we present a community detection algorithm that takes into account the aging and weight of contacts between mobile entities. Our idea originates from message-forwarding operations in opportunistic networks. We evaluate the algorithm on both computer-generated networks and real-world human mobility traces. The result shows that our proposed algorithm can find the communities and detect the changes in their structures over time.

关键词： detection algorithms Humans Aging Computer networks Protein engineering Diseases Social network services Web sites Search engines Information filtering

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Clustering of Short Strings in Large Databases

Clustering of Short Strings in Large Databases

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International Workshop on Database and Expert Systems Applications

作者： Michail Kazimianec Arturas Mazeika Faculty of Computer Science Free University of Bolzano-Bozen Italy Department 5 Max Planck Institut für Informatik Germany

A novel method CLOSS intended for textual databases is proposed. It successfully identifies misspelled string clusters, even if the cluster border is not prominent. The method uses q-gram approach to represent data and a string proximity graph to find the cluster. Contribution refers to short string clustering in text mining, when the proximity graph has multiple horizontal lines or the line is not present.

关键词： Databases detection algorithms Smoothing methods Expert systems Application software Computer science Text mining Tagging Robustness Clustering methods

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A Mnemonic Multiuser Detector Based on Genetic Algorithm in Multicode LAS-CDMA System

A Mnemonic Multiuser Detector Based on Genetic Algorithm in ...

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International Conference on Wireless Communications, Networking and Mobile Computing (WiCom)

作者： Hancheng Liao School of Electronics Jiangxi University of Finance and Economics Nanchang China

Multiple access interference still exists in large area-synchronized code division multiple access (LAS-CDMA) system when the LAS multicode is implemented. The generation of spreading sequences is given. Genetic algorithm (GA) is often used to get the multiuser detection (MUD) gain and its computational complexity is much less than that of the optimum maximum-likelihood (ML) detector. In order to further enhance the detection performance, a type of mnemonic GA detector based on the basic GA method is studied, where a replacement strategy of modified elitism is utilized. Simulation results shows that GA detector with memory can obviously reduce the number of iterations in the recursive process.

关键词： Detectors Genetic algorithms Multiaccess communication Multiuser detection Multiple access interference Computational complexity Spread spectrum communication Computational modeling detection algorithms Frequency

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Inversion algorithm for estimating radio frequency interference characteristics based on kurtosis measurements

Inversion algorithm for estimating radio frequency interfere...

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IEEE International Symposium on Geoscience and Remote Sensing (IGARSS)

作者： Sidharth Misra Christopher Ruf Department of Atmospheric Oceanic and Space Sciences University of Michigan Ann Arbor MI USA

An inversion algorithm is developed to recover power and duty-cycle of incoming Radio Frequency Interference (RFI) signals from kurtosis. The algorithm applies simulated annealing on multiple kurtosis values obtained from different radiometer integration periods. The paper evaluates the performance of the inversion algorithm by performing Monte-Carlo simulations to obtain error statistics. The inversion capability of the algorithm and its robustness against the 50% duty-cycle blind-spot (generally present for the kurtosis detection algorithm) is demonstrated using experimental data.

关键词： Frequency estimation Radiofrequency interference Frequency measurement RF signals Simulated annealing Radiometry Performance evaluation Error analysis Robustness detection algorithms

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Mining Data from Multiple Software Development Projects

Mining Data from Multiple Software Development Projects

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IEEE International Conference on Data Mining Workshops (ICDM Workshops)

作者： H. Wang T.M. Khoshgoftaar K. Gao N. Seliya

A large system often goes through multiple software project development cycles, in part due to changes in operation and development environments. For example, rapid turnover of the development team between releases can influence software quality, making it important to mine software project data over multiple system releases when building defect predictors. Data collection of software attributes are often conducted independent of the quality improvement goals, leading to the availability of a large number of attributes for analysis. Given the problems associated with variations in development process, data collection, and quality goals from one release to another emphasizes the importance of selecting a best-set of software attributes for software quality prediction. Moreover, it is intuitive to remove attributes that do not add to, or have an adverse effect on, the knowledge of the consequent model. Based on real-world software projects' data, we present a large case study that compares wrapper-based feature ranking techniques (WRT) and our proposed hybrid feature selection (HFS) technique. The comparison is done using both threefold cross-validation (CV) and three-fold cross-validation with risk impact (CVR). It is shown that HFS is better than WRT, while CV is superior to CVR.

关键词： Data mining Programming Distributed algorithms Statistical distributions detection algorithms Monitoring Conferences Space technology Computer science NASA

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The classification of a protein from its primary sequence using functional and structural-specific PSSMs in quantitative measurement

The classification of a protein from its primary sequence us...

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IEEE International Conference on Bioinformatics and Biomedicine Workshops (BIBMW)

作者： Kyung Dae Ko Yoo Jin Hong Damian B. van Rossum Randen L. Patterson Department of Biology Pennslyvania State University University Park USA Department of CSE Pennslyvania State University University Park USA

In principle, the amino acid sequence of a protein contains structural, functional, and evolutionary characteristics. Investigation of these characteristics using computational methods provides a powerful resource. However, these methods have limitations in their ability to annotate the characteristics of proteins accurately. In an attempt to overcome this drawback, we have developed a unified computational pipeline, called the Gestalt domain detection algorithm basic local alignment tool (GDDA-BLAST), for measuring the structural, functional and evolutionary characteristics of a protein. The performance of GDDA-BLAST is better than those of other method such as SAM and psi-BLAST in homology detection. Using GDDA-BLAST, we implemented a classification library to find quantitative thresholds capable of inferring protein function. Using this library, we first identified RNA-binding proteins (RBPs) containing structural unique motifs by 2695 expanded position specific scoring metric (PSSM) profiles in a testing dataset with 37 positive and 118 negative sequences. We achieved 100% specificity, 96.8% accuracy, and 86.5% sensitivity. For the specific nucleotide binding folds (dsRNA vs. dsDNA, dsRNA vs. dsDNA, and ssRNA vs. ssDNA), our results exceeded those of obtained using support vector machine (SVM) learning algorithms. Using this method, we also identified 29 and 168 novel RBPs in yeast and human proteomes. We extend our experiment to additional protein functions, such as Ankyrin-repeat (ANK), integral lipid-binding(ILB), and calmodulin(CaM)-binding. For ANK, 449 ANK PSSMs are used to measure 126 negative and 32 postive sequences. And, for ILB and CaM-binding, we had used 24,378 PSSMs to measure 24 negatives and 32 positives, and 820 PSSMs used to measure 17 negatives and 65 positives, respectively. By ROC curve analysis,calmodulin we achieved ~100%, ~93%, ~72% sensitivity at false positive rate ~10%, for ANK, ILB, and CaM-binding classification. The result again con

关键词： Libraries Sensitivity Support vector machines Amino acids Pipelines detection algorithms Protein engineering Testing Machine learning Fungi

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