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international conference of soft computing and pattern recognition (SoCPaR)

作者： Atta-ur-Rahman Salam, Muhammad Hammad Naseem, Muhammad Tahir Muzaffar, Muhammad Zeeshan PMAS Arid Agr Univ BIIT Rawalpindi Pakistan Inst Signals Syst & Soft Comp ISSS Islamabad Pakistan Univ Lahore Blue Area Islamabad Pakistan ISRA Univ SEAS Islamabad Pakistan

ISBN: (纸本)9781479934003

Adaptive communication is becoming requirement of every communication system for effective utilization of available radio resources. In this approach the transmission parameters like code rate, modulation size and available power are dynamically chosen so that the overall system throughput is maximized while certain constraints like bit error rate are satisfied. In this paper a similar constrained optimization problem is solved by optimally choosing the said parameters with the help of Differential Evolution algorithm with a Fuzzy Rule Based System (DE-FRBS) in an OFDM environment. in this proposal the FRBS is used to adapt the code rate and the modulation scheme according to channel state information (CSI) and desired quality of service (QoS) while DE is employed to find the optimum power vector (OPV) to be transmitted over OFDM subcarriers. Product codes and Quadrature Amplitude Modulation (QAM) are used as coding and modulation schemes respectively. Product codes are considered much powerful in terms of error correction capability. Significance of the proposed scheme is shown by the simulations.

关键词： component DE OFDM FRBS BER ACM

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A pattern recognition Method for Scene Sketch Images Using Deep Learning and Its Evaluation 11

A Pattern Recognition Method for Scene Sketch Images Using D...

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Joint 11th international conference on soft computing and Intelligent Systems and 21st international Symposium on Advanced Intelligent Systems (SCIS-ISIS)

作者： Oshima, Kengo Takagi, Noboru Sawai, Kei Masuta, Hiroyuki Motoyoshi, Tatsuo Toyama Prefecture Univ Dept Intelligent Design Engn Toyama Japan

ISBN: (纸本)9781728197326

Many studies on handwritten figure recognition have been published so far. For handwritten graphics in the fields of science and engineering, clear drawing rules are often clear, that is the shapes of the elements are predetermined. On the other hand, there is no drawing rule for sketches such as scene sketches;this makes it difficult to design a feature extractor. Based on this background, in recent years, research on recognition models using deep learning for sketch images has been reported. However, the recognition rate of all the previous research results are about 70% or less. Therefore, in this paper, we propose a new CNN model for recognizing landscape sketch images, and verify its effectiveness by computer experiments. Since there is no benchmark data for landscape sketch images, it cannot be compared with the results of previous studies, but the recognition rate of the CNN model proposed here is about 80%, which is higher than that of previous studies.

关键词： Sketch Understanding Deep Neural Network

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Modular neural networks with applications to pattern profiling problems

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NEUROcomputing 2009年第10-12期72卷 2093-2100页

作者： Tseng, H. Chris Almogahed, Bassam San Jose State Univ Dept Comp Sci San Jose CA 95192 USA

We study the feasibility and the performance of modular design concept as applied to pattern profiling problems using artificial neural network. By decomposing the given pattern profiling problem into smaller modules, it is shown that comparable performance can be achieved with improvement on computation and design complexity. A survey of typical modular neural networks shows that large-scale nonlinear problems can alleviate its dimensionality curse with modular technique. Overview of modular neural networks based on how the problem is modularized through various decomposition and subsequent aggregation is given. A pattern recognition problem for aircraft trajectory prediction using NeuroFuzzy learning with a two stage modular learning design is presented. Decoupled data are used to train respective neural network modules. A genetic algorithm is used to aggregate all the learned modules so that it is ready for online pattern recognition purpose. As compared with the non-modular approach, the modular approach offers comparable prediction performance with significantly lower overall computation time. This study validates that modular design is a promising solution for large-scale soft computing problems. (C) Published by Elsevier B.V.

关键词： Neural networks Modular design soft computing Time-series prediction pattern recognition

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Multivariate Analysis of Text Data from Image Information Acquired by Wearable Device 10

Multivariate Analysis of Text Data from Image Information Ac...

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Joint 10th international conference on soft computing and Intelligent Systems (SCIS) / 19th international Symposium on Advanced Intelligent Systems (ISIS)

作者： Domoto, Eri Shibata, Junko Fukushima, Mizuki Okuhara, Koji Hiroshima Univ Econ Fac Econ Hiroshima Japan Kobe Gakuin Univ Fac Econ Kobe Hyogo Japan Fujitsu Hokuriku Syst Ltd Kanazawa Ishikawa Japan Toyama Prefectural Univ Grad Sch Engn Toyama Japan

ISBN: (纸本)9781538626337

In this study, we obtain life log data from visibility information using smart glass which is a wearable device. In the proposed system, it consists of a text data collection part by cooperation between smart glass and image recognition API and activity recognition part. The activity recognition part incorporates multidimensional scaling analysis method and correspondence analysis for classifying data. As a result of utilizing the development system in real life, it was able to detect similarities and events for behavior from the difference of the object caught on sight.

关键词： Multivariate Analysis Life Log Behavior pattern Text Data Mining

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Adaptive Communication using softcomputing Techniques

Adaptive Communication using Softcomputing Techniques

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international conference of soft computing and pattern recognition (SoCPaR)

作者： Atta-ur-Rahman Qureshi, Ijaz Mansoor Salam, Muhammad Hammad Muzaffar, Muhammad Zeeshan PMAS Arid Agr Univ Rawalpindi Barani Inst Informat Technol Rawalpindi Pakistan Inst Signals Syst & Soft Comp ISSS Islamabad Pakistan Air Univ Dept Elect Engn Islamabad Pakistan ISRA Univ SEAS Islamabad Pakistan Univ Lahore SIT Islamabad Pakistan

ISBN: (纸本)9781479934003

Adaptive communication has gained attention of almost every recent communication system because of its rate enhancement and context aware features. In this concept, different transmission parameters like transmit power, forward error correcting (FEC) code rate and modulation scheme are adaptively chosen according to the channel state information. Consequently, that set of transmission parameters is chosen that maximizes the channel capacity as well as fulfills the power and bit error rate constraints. Finding the optimum value of the said parameters is a highly non-linear problem with huge search space for solution. In this paper, we have investigated Ant Colony Optimization (ACO) in conjunction with a fuzzy rule base system (SA-FRBS) for adaptive coding, modulation and power in an orthogonal frequency division multiplexing environment. Proposed scheme is compared with Simulated Annealing and FRBS (SA-FRBS) assisted adaptive coding modulation and power scheme as well as with the fixed power scheme. Superiority of proposed scheme is shown by the simulations.

关键词： component ACO Simulated Annealing OFDM FRBS BER Adaptive Modulation and Coding

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Advanced Deep Neural Networks for pattern recognition: An Experimental Study 8th

Advanced Deep Neural Networks for Pattern Recognition: An Ex...

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8th international conference on soft computing and pattern recognition (SoCPaR) / 8th international conference on Computational Aspects of Social Networks (CASoN)

作者： Padmanabhan, Jayashree Premkumar, J. Melvin Jose Anna Univ Madras Inst Technol Madras 600044 Tamil Nadu India Google Inc Software Engn Intern Mountain View CA 94043 USA

ISBN: (纸本)9783319606187;9783319606170

Difficulty in pattern recognition is perceptible and neural networks approach the problem by way of learning from similar known patterns. Interest in Neural Networks started in the early 1980s when they were deemed to effectively model the human thought process. Speech recognition which first used Artificial Neural Networks (ANNs) to model the states of a Hidden Markov Models (HMMs) later started using Gaussian Mixture Models (GMMs). GMM-HMM systems have been the standard until recently when a new concept of Deep Neural Networks (DNNs) pre-trained using Restricted Boltzmann Machines (RBMs) came into existence. The discriminative capability of the resulting DNN is found to improve the performance of the recognition systems. The experimental work with DNN for recognizing patterns in handwriting and speech corpus has been carried out. In this work we implemented Deep Neural Networks for the above tasks and the pre trained DNN has been used for extracting bottleneck features and hereby improving the performance of the baseline systems with respect to recognition errors.

关键词： Deep Neural Networks Boltzmann machine Speech recognition Artificial Neural Networks Machine learning

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Searching for a Similar Time Series Fragment when Solving a recognition Problem via the Example of an Electrocardiogram 20

Searching for a Similar Time Series Fragment when Solving a ...

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20th IEEE international conference on soft computing and Measurements (SCM)

作者： Begeneev, Vladislav Yu. Shmidt, Igor A. PNRPU Electrotech Dept Perm Russia

ISBN: (纸本)9781538618103

The article is devoted to searching for a time series fragment of an electrocardiogram. The purpose of this study is to identify defects in the work of the human heart. First of all, the desired pattern is selected. Next, a sampling window is arbitrarily selected in the electrocardiogram from the entire time series. The ST-index is used to find the fragment that looks like the given pattern. As a result of this study, a technique for finding the fragment was developed. At the end of the presented work, the task is formulated to conduct further research optimizing the developed methodology.

关键词： cardio signal time series fast Fourier transform electrocardiogram wave pattern ST-index

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pattern recognition Based on the Nonparametric Kernel Regression Method in A-share Market

Pattern Recognition Based on the Nonparametric Kernel Regres...

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international conference on soft computing Techniques and Engineering Application (ICSCTEA)

作者： Sun, Huaiyu Zhu, Mi He, Feng Wuhan Univ Econ & Management Sch Wuhan 430072 Peoples R China China Investment Secur Co Ltd Res Dept Shenzhen Peoples R China UBS SDIC Fund Management Co Ltd Prod Design Dept Shenzhen Peoples R China

ISBN: (纸本)9788132216957;9788132216940

Fourteen kinds of technical pattern in A-share market have been automatically identified in this paper, using nonparametric kernel regression method and quantitative recognition rules that are constrained and improved to make the model more feasible and effective for investment practice. K-S test shows that the distribution of the stock yield following the recognized patterns statistically differs from that of random sampling. Clustering analysis also suggests that most of the identified technical patterns have distinguishable effects on the subsequent stock price movement. These findings provide useful guidance for the development of innovative investment models in high-frequency automatic stock trading.

关键词： Technical pattern recognition Nonparametric kernel regression

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Application of Multidimensional Data Visualization in Creation of pattern recognition Systems 3

Application of Multidimensional Data Visualization in Creati...

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3rd international conference on Man-Machine Interactions (ICMMI)

作者： Jamroz, Dariusz AGH Univ Sci & Technol PL-30059 Krakow Poland

ISBN: (纸本)9783319023090

The paper presents the application of multidimensional data visualization to obtain the views of 5-dimensional space of features created by recognition of printed characters. On the basis of these views it was stated that the features chosen to construction of features space are sufficient to correct recognition process. This is the significant help by constructing the recognition systems because the correct selection of objects properties on the basis of which the recognition should occur is one of the hardest stages.

关键词： multidimensional visualization pattern recognition

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Review of Artificial Immune System in Web Personalization

Review of Artificial Immune System in Web Personalization

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international conference of soft computing and pattern recognition

作者： Rastegari, Hamid Shamsuddin, Siti Mariyam Univ Technol Malaysia Fac Comp Sci & Informat Syst Skudai Malaysia

ISBN: (纸本)9781424453306

This paper is a review on knowledge discovery in the field of web mining for the benefit of research on the personalization of web-based information services. The essence of personalization is the adaptability of information systems to the needs of their users. This issue is becoming increasingly important on the Web, as non-expert users are overcame by the quantity of information available online. This article investigates the application of artificial immune systems (AIS) to knowledge discovery as a web personalization tool. AIS are thought to confer the adaptability and learning required for this task.

关键词： Web Personalization Artificial Immune System Web Usage Mining pattern Discovery Clonal Selection

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