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检索条件"主题词=Detection algorithms"

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The New detection algorithms for Network Traffic Anomalies

The New Detection Algorithms for Network Traffic Anomalies

引用

International Conference on Networking (ICN)

作者： Jun Lv Xing Li Tong Li Acad. of Armoured Forced Eng. Beijing China Education and Research Network Tsinghua University Beijing China Academy of Armored Forces Engineering Beijing China The Academy of Armoured Forced Engineering Beijing China

Network traffic anomaly detection is a difficult problem in network management. This paper presents a wavelet generalized likelihood ratio (WGLR) algorithm and an error performance detection (EPD) algorithm to solve this problem. WGLR algorithm combines generalized likelihood ratio (GLR) algorithm and wavelet transform method, and captures the failure point in real time. Error performance detection (EPD) algorithm is based on the prediction error of the traffic model and regards the error as the statistical variable, comparing with the threshold, which will detect the anomalous change in the signal without test window delay. Simulation and network traffic experiment has demonstrated that the algorithm has better performance in fault detection.

关键词： detection algorithms Telecommunication traffic Traffic control Testing Change detection algorithms Fault detection Wavelet transforms Delay Engineering management Predictive models

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A Neural Network-Based Optimal Nonlinear Fusion of Speech Pitch detection algorithms

A Neural Network-Based Optimal Nonlinear Fusion of Speech Pi...

引用

International Conference on Knowledge-Based Engineering and Innovation (KBEI)

作者： Ziba Imani Seyed Jahanshah Kabudian Department of Computer Engineering and Information Technology Razi University Kermanshah Iran

Fundamental frequency estimation is one of the most important issues in the field of speech processing. An accurate estimate of the fundamental frequency plays a key role in the field of speech and music analysis. So far, various methods have been proposed in the time- and frequency-domain. However, the main challenge is the strong noises in speech signals. In this paper, to improve the accuracy of fundamental frequency estimation, we propose a method for optimal nonlinear combination of fundamental frequency estimation methods, in noisy signals. In this method, to discriminate voiced frames from unvoiced frames in a better way, the Voiced/Unvoiced (V/U) scores of four pitch detection methods are combined with nonlinear fusion. These methods are: Autocorrelation (AC), Yin, YAAPT and SWIPE. After identifying the Voiced/Unvoiced label of each frame, the fundamental frequency (F 0 ) of the frame is estimated using the SWIPE method. The optimal function for nonlinear combination is determined using Multi-Layer Perceptron (MLP) neural network (NN). To evaluate the proposed method, 10 speech files (5 female and 5 male voices) are selected from the PTDB-TUG standard database and the results are presented in terms of GPE, VDE, PTE and FFE standard error criteria. The results indicate that our proposed method relatively reduced the aforementioned criteria (averaged in various SNRs) by 25.06%, 20.92%, 13.94%, and 25.94% respectively, which demonstrate the effectiveness of the proposed method in comparison to state-of-the-art methods.

关键词： Noise measurement Estimation detection algorithms Frequency estimation Standards Mathematical model Correlation

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On the Effect and Robustness of Zero-crossing detection algorithms in Simulation of Hybrid Systems Jumping on Surfaces

On the Effect and Robustness of Zero-crossing Detection Algo...

引用

American Control Conference

作者： David A. Copp Ricardo G. Sanfelice Department of Aerospace and Mechanical Engineering University of Arizona 1130 N. Mountain Ave AZ 85721 USA

ISBN: (纸本)9781457710957

Motivated by the fragility to perturbations of hybrid systems jumping on surfaces and the robustifying capabilities of zero-crossing detection algorithms, we propose a hybrid simulator model with incorporated zero-crossing detection. First, we reveal the effect of measurement noise and of discretization to hybrid systems jumping on surfaces. We prove that, under mild regularity conditions, zero-crossing detection algorithms have a robustifying effect on the original system. Then, we argue that, rather than computing the solutions to the discretization of the fragile nominal model, integration schemes with zero-crossing detection actually compute the solutions of a robustified version of the original model. We propose a mathematical model for the hybrid system with incorporated zero-crossing detection as well as a hybrid simulator for it. We show that both the model and simulator are not only robust, but also that the hybrid simulator preserves asymptotic stability properties, semiglobally and practically (on the step size), of the original system. An example illustrates the ideas and results throughout the paper.

关键词： detection algorithms hybrid systems zero crossings Noise measurement simulator Discretization step size Jumping Fragility simulating

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Comparative Analysis of Facial Affect detection algorithms

Comparative Analysis of Facial Affect Detection Algorithms

引用

IEEE International Conference on Systems, Man and Cybernetics

作者： Ashin Marin Thomas Myounghoon Jeon Virginia Tech Blacksburg Virginia

ISBN: (数字)9781728185262

ISBN: (纸本)9781728185279

There has been much research on facial affect detection, but many of them fall short on accurately identifying expressions, due to changes in illumination, occlusion, or noise in uncontrolled environments. Also, not much research has been conducted on implementing the algorithms using multiple datasets, varying the size of dataset and the dimension of each image in the dataset. Our ultimate goal is to develop an optimized algorithm that can be used for real-time affect detection in automated vehicles. To this end, in this study we implemented the facial affect detection algorithms with various datasets and conducted a comparative analysis of performance across the algorithms. The algorithms implemented in the study included a Convolutional Neural Network (CNN) in Tensorflow, FaceNet using Transfer Learning, and Capsule Network. Each of these algorithms was trained using the three datasets (FER2013, CK+, and Ohio) to get the predicted results. The Capsule Network showed the best detection accuracy (99.3%) with the CK+ dataset. Results are discussed with implications and future work.

关键词： Image resolution Lighting Gray-scale Prediction algorithms Real-time systems detection algorithms Vehicles

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Pitch detection algorithms and Voiced/Unvoiced Classification for Noisy Speech

Pitch Detection Algorithms and Voiced/Unvoiced Classificatio...

引用

International Conference on Systems, Signals and Image Processing, IWSSIP

作者： Ekaterina Verteletskaya Kirill Sakhnov Boris Simak Department of Electrical Engineering Czech Technical University Prague Czech Republic

This paper describes pitch tracking techniques, which combine voiced/unvoiced classification and pitch estimation based on cepstral analysis, time autocorrelation, spectro-temporal autocorrelation (STA) and average magnitude difference function (AMDF). Pre- and post processing techniques improving performance of pitch detection algorithms (PDAs) are also presented. PDAs have been evaluated by telephone speech signals, corrupted by additive noise, in order to provide comparison and demonstrate their performance and robustness. Speech signals used for evaluation were taken from the Czech telephone speech database consisted of 5 male and 5 female speakers.

关键词： detection algorithms Speech analysis Autocorrelation Personal digital assistants Telephony Cepstral analysis Speech enhancement Additive noise Noise robustness Databases

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Channel estimation and data detection algorithms for UWB multiuser communications

Channel estimation and data detection algorithms for UWB mul...

引用

International Symposium on Wireless Pervasive Computing (ISWPC)

作者： Alessandro Barbieri Fabrizio Pancaldi Giorgio M. Vitetta Department of Information Engineering University of Modena and Reggio Emilia and INFM Modena Italy Department of Science and Methods for Engineering University of Modena and Reggio Emilia and INFM Reggio Emilia Italy

ISBN: (纸本)9781424468553;9781424468584

In this paper, a novel ultrawideband system for multiuser data communications is proposed. At the transmit side multiple users are allowed to send pulse position modulated signals in a synchronized fashion exploiting a given frequency subband in the same time intervals. Overlapped data frames sent by distinct users include low data rate training sequences with different repetition periods. This transmission strategy, known as rate division multiple access in the technical literature, allows to ease the first two fundamental tasks at the receive side, namely joint channel estimation and timing synchronization. Channel estimates are exploited by a multiuser detector based on the Viterbi algorithm and separating the contribution generated by the user of interest from those produced by all the other co-channel users. Numerical results evidence that the proposed solution can offer an efficient usage of the available spectrum at the price of a limited complexity.

关键词： Channel estimation detection algorithms Pulse modulation Data engineering Frequency synchronization Multiple access interference Ultra wideband technology Viterbi algorithm Payloads Pervasive computing

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Reduced-complexity detection algorithms for systems using multi-element arrays

Reduced-complexity detection algorithms for systems using mu...

引用

IEEE Conference and Exhibition on Global Telecommunications (GLOBECOM)

作者： X. Li H.C. Huang A. Lozano G.J. Foschini Bell Laboratories Lucent Technologies Inc. Holmdel NJ USA

In BLAST (Bell-Laboratories LAyered Space Time) systems, multiple transmit and receive antennas are employed to achieve very high spectral efficiencies. The ideal detection method for such systems is the maximum-likelihood (ML) algorithm. However, the ML complexity increases exponentially with the number of transmit antennas and the number of bits per modulation symbol. A reduced-complexity detection method has been suggested, using ordered successive interference cancellation. We consider two other suboptimum techniques: channel-based adaptive group detection and multistep reduced-constellation detection. The goal is to reduce the two aforementioned complexity exponentials. The algorithms efficiently combine linear processing with local ML search. We limit the complexity by maintaining small ML searching areas, while maximizing the performance under the complexity constraint by optimizing the front-end linear processing and the selection of the search areas.

关键词： detection algorithms Receiving antennas Fading Maximum likelihood detection Space technology Interference cancellation Signal detection Transmitting antennas Additive white noise Multiuser detection

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Performance evaluation of object detection algorithms

Performance evaluation of object detection algorithms

引用

International Conference on Pattern Recognition

作者： V.Y. Mariano Junghye Min Jin-Hyeong Park R. Kasturi D. Mihalcik Huiping Li D. Doermann T. Drayer Pennsylvania State University University Park PA USA University of Maryland College Park MD USA Department of Defense Fort Meade MD USA

The continuous development of object detection algorithms is ushering in the need for evaluation tools to quantify algorithm performance. In this paper a set of seven metrics are proposed for quantifying different aspects of a detection algorithm's performance. The strengths and weaknesses of these metrics are described. They are implemented in the Video Performance Evaluation Resource (ViPER) system and will be used to evaluate algorithms for detecting text, faces, moving people and vehicles. Results for running two previous text-detection algorithms on a common data set are presented.

关键词： Object detection Shape Face detection detection algorithms Vehicles Video sequences Measurement Educational institutions Humans Eyes

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Evaluating endpoint detection algorithms for isolated word from Malay parliamentary speech

Evaluating endpoint detection algorithms for isolated word f...

引用

International Conference on Information Retrieval & Knowledge Management (CAMP)

作者： Noraini Seman Zainab Abu Bakar Nordin Abu Bakar Haslizatul Fairuz Mohamed Nur Atiqah Sia Abdullah Prasanna Ramakrisnan Sharifah Mumtazah Syed Ahmad Department of Computer Science Universiti Teknologi MARA (UiTM) Shah Alam Selangor MALAYSIA Department of System and Network Department Universiti Tenaga Nasional (UNITEN) Kajang Selangor MALAYSIA

This paper presents the endpoint detection approaches specifically for an isolated word uses Malay spoken speeches from Malaysian Parliamentary session. Currently, there are 7,995 vocabularies of utterances in the database collection and for the purpose of this study; the vocabulary is limited to ten words which are most frequently spoken selected from ten speakers. Endpoint detection, which aims to distinguish the speech and non-speech segments of digital speech signal, is considered as one of the key preprocessing steps in speech recognition system. Proper estimation of the start and end of the speech (versus silence or background noise) avoids the waste of speech recognition evaluations on preceding or ensuing silence. In this study, the endpoint detection and speech segmentation task is achieved by using the short-time energy (STE) and short-time zero crossing (STZC) measures and combination of both approaches. As a result, the Hidden Markov Model (HMM) recognizer derived the recognition accuracy rate of 91.4% for combination of both algorithms, if compared only 86.3% for STE and 82.1% for STZC rate alone. The experiments show that there are many problems arise where there are still misdetection of word boundaries for the words with weak fricative and nasal sounds. Other obstacles issues such as speaking styles or mood of speaking can also cause the recognition performance.

关键词： detection algorithms Speech analysis Vocabulary Speech recognition Hidden Markov models Databases Speech enhancement Background noise Energy measurement Mood

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Comparison of different detection algorithms for OFDM-CDMA in broadband Rayleigh fading

Comparison of different detection algorithms for OFDM-CDMA i...

引用

IEEE Conference on Vehicular Technology (VTC)

作者： T. Muller H. Rohling R. Grunheid Institute of Telecommunications Technical University of Braunschweig Braunschweig Germany

The orthogonal frequency division multiplexing (OFDM) transmission technique applied in a multipath environment has a bit error rate (BER) comparable with a narrowband radio channel because the fading of each subcarrier is frequency-nonselective. To overcome this behavior and to reduce the BER a combination of OFDM and CDMA has been previously proposed. In this case the information bits are spread over many subcarriers. The present authors discuss the performance of OFDM-CDMA with BPSK or QPSK signalling over a frequency-selective Rayleigh fading channel. An important question is the detection strategy in an OFDM-CDMA system. The authors make a quantitative comparison of different detection algorithms: conventional correlation (equal gain, EGC), orthogonality restoring correlation (ORC), ORC with a threshold in order to suppress subcarriers with low signal strength (TORC) and an iterative improvement based on a maximum likelihood approach. With TORC and an optimal threshold a gain of more than 8 dB over conventional OFDM can be obtained at p/sub b/=10/sup -3/, if the fading of subcarriers is uncorrelated.

关键词： detection algorithms OFDM Bit error rate Fading Narrowband Multiaccess communication Binary phase shift keying Quadrature phase shift keying Signal restoration Iterative methods

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