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Analysis of least mean square and recursive least squared adaptive filter algorithm for speech enhancement application 3rd

Analysis of least mean square and recursive least squared ad...

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3rd international conference on Next Generation computing Technologies, NGCT 2017

作者： Bachute, Mrinal Kharadkar, R.D. Savitribai Phule University PuneMaharashtra India G.H. Raisoni Institute of Engineering and Technology Wagholi PuneMaharashtra India

ISBN: (纸本)9789811086564

Speech enhancement is a vital area of research, the performance of speech based human machine applications such as automatic speech recognition system, in car communication depends on the quality of speech communicated. Different methodologies have been used by various researchers to improve the quality of speech signal. In this paper an attempt is made to analyze the performance of Least Mean Square (LMS) and Recursive Least Squared (RLS) adaptive filter algorithm for speech enhancement application. The performance indices used for the evaluations is Mean Square Error (MSE), Signal to Noise Ration (SNR) and execution time. The detail analysis is done and experimentally the results are validated and certain modifications are suggested in the algorithm. The experimentation revels that LMS have fast convergence than RLS. The computational complexity of RLS is very high as compared to LMS. © Springer Nature Singapore Pte Ltd. 2018.

关键词： Speech enhancement

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Temporal signature mining for network intrusion detection using TEMR

Temporal signature mining for network intrusion detection us...

引用

international conference on Emerging Technologies in Data Mining and Information Security, IEMIS 2018

作者： Mawla, Tanjila Dutta, Sharmishtha Rabbi, Md. Forhad North East University Bangladesh Telihaor Sheikhghat Sylhet3100 Bangladesh Metropolitan University Zindabazar Sylhet3100 Bangladesh Shahjalal University of Science & Technology Kumargaon Sylhet3114 Bangladesh

ISBN: (纸本)9789811315008

Network intrusion detection is being a big challenge to combine the network security with the growing speed of data transmission. Traditional data mining approaches were widely used to detect intrusions though having some drawbacks. But there remain some needs of the application of temporal data mining techniques on network intrusion detection as the flow of network data is continuous over time. This paper proposes the idea of applying a framework which is based on doubly sparse convolutional matrix that is closely related to nonnegative matrix factorization to identify the hidden patterns of events. One-sided convolution of two nonnegative matrices shows the convergence of the framework. There is an observation about applying the algorithm on network intrusion detection (NID), and this is how β-divergence increases and decreases with the consideration of a different number of data. The successful minimization of β-divergence can lead to categorizing attack and normal activities found in a dataset containing a packet of network data. © Springer Nature Singapore Pte Ltd. 2019.

关键词： Network security

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Stability Analysis of Large-Scale Agent-Based Systems

Stability Analysis of Large-Scale Agent-Based Systems

引用

international conference on Innovative computing, Information and Control (ICICIC)

作者： A.A. Jamshidifar A. Afshar Iranian Research Organization for Science and Technology Amirkabir University of Technology슠 Iran Amirkabir University of Technology슠 Iran

The problem of stability analysis of agent and agent-based systems is of great interest. This is even more important for large-scale agent-based systems (LSABS), where there are a high number of interacting agents. This paper proposes a new approach to tackle this problem. In the proposed approach, agent is assumed to be a hybrid entity with discrete modes and continuous evolution within each mode, and therefore a hybrid stability analysis is employed. At the system level, an energy concept is used for the system stability analysis. An example is given to support the proposed approach

关键词： Stability analysis Large-scale systems Statistical analysis convergence Power system modeling Power system analysis computing Predictive models Multiagent systems Equations Mathematical model

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Harmony search optimization algorithm based on normal cloud

引用

2nd international conference on Opto-Electronics Engineering and Materials Research, OEMR 2013

作者： Wang, Li Fu Kong, Zhi Wang, Xin Gang College of Control Engineering Northeastern University at Qinhuangdao Qinhuangdao China

ISBN: (纸本)9783037857731

The pitch adjusting rate (PAR) is an important parameter in harmony search algorithm, which indicates that the algorithm will choose a neighboring value with a probability. The traditional harmony search algorithm uses fixed value for PAR. However, PAR should be increased when all objective values are centralized and decreased when the function values are scattered in the solution space. In this paper, a new cloud harmony search algorithm (CHS) is proposed. We introduce cloud model theory to adjust the value PAR in the harmony search to improve the global search ability and make faster convergence speed of the algorithm. The improved harmony search algorithm is tested on some benchmark functions and the results are compared with the result of the traditional harmony search. Experimental results indicate that the improved harmony search algorithm has a good performance in the global search ability and convergent speed. © (2013) Trans Tech Publications, Switzerland.

关键词： Cloud computing

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Understanding Clique Formation in Social Networks - An Agent-Based Model of Social Preferences in Fixed and Dynamic Networks 16th

Understanding Clique Formation in Social Networks - An Agen...

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16th international conference on Social computing, Behavioral-Cultural Modeling and Prediction and Behavior Representation in Modeling and Simulation, SBP-BRiMS 2023

作者： Arya, Pratyush Srivastava, Nisheeth Indian Institute of Technology Kanpur Kanpur208016 India

ISBN: (纸本)9783031431289

This paper presents results from in silico experiments trying to uncover the mechanisms by which people both succeed and fail to reach consensus in networked games. We find that the primary cause for failure in such games is preferential selection of information sources. Agents forced to sample information from randomly selected fixed neighborhoods eventually converge to a consensus, while agents free to form their own neighborhoods and forming them on the basis of homophily frequently end up creating balkanized cliques. We also find that small-world structure mitigates the drive towards consensus in fixed networks, but not for self-selecting networks. Preferentially attached networks appear to show the highest convergence to one color, thereby showing resilience to balkanization of opinion in self-selecting networks. We conclude with a brief discussion of the implications of our findings for the representation of behavior in socio-cultural modeling. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Autonomous agents

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Algorithmically transitive network: Learning padé networks for regression 7th

Algorithmically transitive network: Learning padé networks ...

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7th international ICST conference on Bio-Inspired Models of Network, Information, and computing Systems, BIONETICS 2012

作者： Suzuki, Hideaki National Institute of Information and Communications Technology 588-2 Iwaoka Iwaoka-cho Nishi-ku Kobe651-2492 Japan

ISBN: (纸本)9783319069432

The learning capability of a network-based computation model named "Algorithmically Transitive Network (ATN)" is extensively studied using symbolic regression problems. To represent a variety of functions uniformly, the ATN’s topological structure is designed in the form of a truncated power series or a Padé approximant. Since the Padé approximation has better convergence properties than the Taylor expansion, the ATN with the Padé can construct an algebraic function with a relatively small number of parameters. The ATN learns with the standard back-propagation algorithm which optimizes intra-network parameters by the steepest descent method. Numerical experiments with benchmark problems show that the ATN in the form of a Padé approximant has better learning capability than linear regression analysis in a power series, the standard multi-layered neural network with the back-propagation learning, the support vector machine using the radial basis function as kernel, or the simple genetic programming. © Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2014.

关键词： Genetic programming

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3D Trajectory Planning of Underwater Vehicle Based on DPACO Algorithm

3D Trajectory Planning of Underwater Vehicle Based on DPACO ...

引用

international conference on Guidance, Navigation and Control, ICGNC 2020

作者： Zirong, Jin Zhilong, Zou Liang, Zhang School of Science Wuhan University of Technology Wuhan Hubei430070 China

ISBN: (纸本)9789811581540

In trajectory planning space, the dynamic programming algorithm is characterized by capabilities of computing and optimization. However, in 3D trajectory planning, as the planning space expands, the number of grid points increases faster, and time complexity of the dynamic programming algorithm is$$O\left({n^{3} } \right)$$. It often leads to a "Curse of dimensionality" phenomenon, which lowers its computational efficiency drastically. To solve this problem, this paper divides the entire planning space into stages based on Bellman's optimality principle. A dynamic programming-ant colony algorithm is proposed by using ant colony algorithm in each stage for optimization, and dynamic programming algorithm for global planning. The global optimization ability of the algorithm is verified through its convergence analysis. Moreover, based on a comparative analysis of simulation experiments, it shows that the improved algorithm proposed in this paper is more efficient than the dynamic programming algorithm and ant colony algorithm alone, and can be used to plan a global optimal solution. © 2022, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Global optimization

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Research on lightweight detection algorithm of Infrared Image based on YOLOv5 4

Research on lightweight detection algorithm of Infrared Imag...

引用

4th international conference on Advanced Algorithms and Signal Image Processing, AASIP 2024

作者： Zhang, Wenyi Mo, Hongwei Wu, Songling Li, Xiaomin Harbin Engineering University School of Intelligent Science and Engineering Harbin150000 China Beijing Aerospace Automatic Control Institute Beijing100854 China National Key Laboratory of Science and Technology on Aerospace Intelligence Control Beijing100854 China

ISBN: (数字)9781510682818

ISBN: (纸本)9781510682801

At present, infrared image can show good detection effect in complex environment because of its unique imaging characteristics, which brings a lot of convenience to people's production and life. However, because the infrared image contains a great lot of unnecessary information, it has great requirements for computing power and memory capacity, so it is challenging to satisfy the demands of real-time detection on resource-constrained portable mobile devices. To solve this problem, this paper proposes a refined lightweight algorithm built upon the YOLOv5, which changes the backbone network of the model to GhostNet network, introduces CA attention mechanism into the model to improve the detection effect of small targets, and changes the loss function of the model to Focal-EIoU loss function to improve the location effect of the boundary box and quicken the model's rate of convergence. Then replace the conventional convolution used in the sampling process of the model with the space-to-depth convolution module, in order to enhance the model's detection performance on low-resolution images and enable the extraction of more feature information. According to the experimental results, the enhanced detection algorithm is just 1% less than the initial YOLOv5 algorithm, and the model volume and floating point calculation are reduced by 31.9% and 36% respectively. This is better suited for deployments that are lightweight. © 2024 SPIE.

关键词： Convolution

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Energy Consumption In Mobile computing

Energy Consumption In Mobile Computing

引用

international conference on Electronics, Communications and computing

作者： Ricardo Isidro Ramirez Erika Hernandez Rubio Amilcar Meneses Viveros SEPI - ESCOM - IPN SEPI - ESCOM IPN CINVESTAV - IPN

ISBN: (纸本)9781467361569

Mobile devices users have risen in recent years, by convergence of functionality and technology on it. Mobile devices also appear in market as interactive devices where users expects short-time response, usability and functionality. That convergence of digital entertainment, mobile communication technologies, and a set of new capabilities, becomes requirements for mobile application developers and hardware architects, thus both professionals have the dilemma of offer low power consumption and high performance on it. However, both concepts are opposite each other. That means, if I get a great performance, probably have attached high power consumption. Programmers have found in parallel computing, multithreading programming, and process scheduling, the way to achieve more efficiency in their programs. Moreover, hardware architects have found in multicore processors the way to achieve better performance and low-power consumption. This work wants to join both solutions and check if we can achieve less response time in applications and processes, and get a balance between performance and energy consumption.

关键词： Energy Consumption Mobile computing Parallel computing Multithreading Systems-On-Chip

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A Multi-objective Approach to Study the Effects of Ball Race Conformity on Optimum Design of Rolling Element Bearing Using Metaheuristics 3rd

A Multi-objective Approach to Study the Effects of Ball Race...

引用

3rd international conference on Advanced computing and Intelligent Engineering, ICACIE 2018

作者： Panda, S.N. Panda, S. Khamari, D.S. Department of Production Engineering B.I.T. SindriJharkhand828123 India Department of Mechanical Engineering V.S.S. University of Technology BurlaOdisha768018 India Department of Mechanical Engineering Govt. College of Engineering KalahandiOdisha766002 India

ISBN: (纸本)9789811514821

One of most critical performance parameters of deep groove ball bearing is the achievable highest fatigue life. The life of the bearing may be affected by more than one factor as types of lubrication, thermal attributes, etc. This present work emphasizes on optimization of life factors, life of bearing along with dynamic load capacity using metaheuristic algorithm based upon the particle swarm methodology (PSO). The two objectives as life factor and dynamic load capacity have been simultaneously optimized using a multi-objective approach under realistic constraint conditions, and also for efficient constraint handling, penalty function method has been used. Right here for formulation of life factors, critical assumptions of operating condition, reliability and materials and processing are being considered. From the above assumptions, it is also considered that the total bearing system is following a series combination of subsystems. A convergence study has been applied to the stated optimization problem. The outcome of this multi-objective approach shows the better efficacy and generosity of the particle swarm algorithm, which can also be implemented for future engineering problems. © 2020, Springer Nature Singapore Pte Ltd.

关键词： Dynamic loads

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