检索结果-内蒙古大学图书馆

International Joint Conference on Neural Networks (IJCNN)

作者： Machireddy, Amrutha Garani, Shayan Srinivasa Indian Inst Sci Dept Elect Syst Engn Bengaluru 560012 India

ISBN: (纸本)9781728119854

Error correction codes such as low density parity check (LDPC) codes are popularly used to enhance the performance of digital communication systems. The current decoding framework relies on exchanging beliefs over a Tanner graph, which the encoder and decoder are aware of. However, this information may not be available readily, for example in covert communication. The main idea of this paper is to build a neural network to learn the encoder mappings in the absence of knowledge of the Tanner graph. We propose a scheme to learn the mappings using the back propagation algorithm. We investigate into the choice of different cost functions and the number of hidden neurons for learning the encoding function. The proposed scheme is capable of learning the parity check equations over a binary field towards identifying the validity of a codeword. Simulation results over synthetic data show that our algorithm is indeed capable of learning the encoder mappings and identifying the parity check equations.

关键词： Error correction codes linear block codes low density parity check codes back propagation algorithm

来源：评论

学校读者我要写书评

暂无评论

Optical character recognition using template matching and back propagation algorithm

Optical character recognition using template matching and ba...

引用

IEEE International Conference on Inventive Computation Technologies (ICICT)

作者： Desai, Swapnil Singh, Ashima Thapar Univ CSED Patiala Punjab India

Building an effective methodology to detect characters from images with less error rate is the great task. Our aim is to furnish such an algorithm that will be able to generate error free recognition of text from the given input image which will help in document digitizing and prevention to the hand written text recognition. OCR has been in the intensive research topic for more than 4 decades, it is probably the most time consuming and labor intensive work of inputting the data through keyboard. This paper discuss about mechanical or electronic conversion of scanned images, text which contain graphics, image captured by camera, scanned images and the recognition of images where characters may be broken or smeared. The optical character recognition is the desktop based application developed using Java IDE and mysql as a database. We have gain 91.82% accuracy when applied on different data sets, in pre-processing we used different techniques to remove noise from the image in post processing we used dictionary for the characters which are not recognized during classification, in classification we have used the back propagation algorithm for the training of neural network, feature extraction has been performed by template matching and hamming distance. All the algorithms have been developed in java technology.

关键词： artificial intelligence back propagation algorithm template matching ocr machine learning java api

来源：评论

学校读者我要写书评

暂无评论

Analysis on the Parameter of back propagation algorithm with Three Weight Adjustment Structure for Hand Written Digit Recognition

Analysis on the Parameter of Back Propagation Algorithm with...

引用

10th International Conference on Service Systems and Service Management (ICSSSM)

作者： Kaensar, Chayaporn Ubon Ratchathani Univ Fac Sci Dept Math Stat & Comp Sci Warin Chamrap Ubonratchathani Thailand

ISBN: (纸本)9781467348430

Recently a commonly used method for Recognition of Handwritten Digit Application based on back propagation Neural Network (BPNN) has been widely applied. However, the original algorithm and its modifications contains a number of free parameters which affect particular networks differently and the slight error rate on the selection of these parameters can cause problems. Thus, this paper presents the effect of input parameters on BPNN with three different structures including Simple back propagation, back propagation with momentum terms and back propagation using conjugate gradient descent methods. To do so, this paper determined different parameters such as learning rate, momentum term or even the number of units in the hidden layer that exist in each structure. The data of UCI database is used for experiment in MATLAB program. The result showed that the back propagation with momentum term could perform very well leading to a recognition rate of 99%. The Simple algorithm obtained high recognition rate but it needed to increase learning rate, while back propagation using conjugate gradient descent could provide high result in case of improving hidden neural nodes. Thus, the result confirmed that adjustment of the relevant parameters are significant to obtain better recognition effect and higher accuracy.

关键词： component Handwritten Digit Recognition back propagation algorithm Learning Rate Momentum Term MATLAB

来源：评论

学校读者我要写书评

暂无评论

Forecasting of Power in Wind Energy Based on back propagation algorithm in Neural Networks

Forecasting of Power in Wind Energy Based on Back Propagatio...

引用

Amity International Conference on Artificial Intelligence (AICAI)

作者： Ramaswamy, Swaroop Amity Univ Dubai Dept Elect & Elect Engn Dubai U Arab Emirates

ISBN: (纸本)9781538693469

This paper presents the forecasting of wind energy using neural networks based on the speed and the rotational speed of the rotor. The wind power mainly depends on the velocity of the wind, density, and swept area of the wind mill which depends on the radius of the rotor. The power also depends on the efficiency of the motor, gear mechanisms. Hence the power varies according to the various parameters which makes the model non-linear. In this paper neural network is used to predict the output from the previous set of data. A new set of data is chosen and tested for the accuracy. It can be seen that the back propagation algorithm in neural network is able to classify the power output based on the speed of the rotor and the wind velocity.

关键词： Neural Networks back propagation algorithm Forecasting Wind Energy

来源：评论

学校读者我要写书评

暂无评论

Super resolution of Astronomical Objects using back propagation algorithm

Super resolution of Astronomical Objects using Back Propagat...

引用

IEEE International Conference on Inventive Computation Technologies (ICICT)

作者： Mhatre, Heena Bhosale, Varsha Vidyalankar Inst Technol Dept Informat Technol Bombay Maharashtra India

ISBN: (纸本)9781509012855

In the past years modern arithmetical methods for image investigation have led to a rebellion in many fields, from computer vision to scientific imaging. Though, some recently developed image processing techniques successfully oppressed by other sections have been infrequently, if ever, experimented on celestial observations. Here we present a new idea of super resolution of Astronomical objects using back propagation algorithm."Super-resolution " is efficient in improving the excellence of analysis of diffused sources formerly unobserved by the background noise, efficiently rising the depth of obtainable observations. Higher-resolution image out of a set of low resolution frames can be obtained through super-resolution. Super-resolution is viable only for point sources which have negligible dimensions, then for wide-ranging objects the knowledge about intensity vacillation at angular prevalence is irreversibly mislaid. Again obtaining super resolved image for extended sources(e.g. comets, meteoroids, etc) is a new challenge if the speed of the object is very high. Acquiring High resolution images of celestial objects from ground based telescopes is intricate and often requires computational post processing techniques to remove blur caused by atmospheric commotion. Even images obtained through satellite imaging are compressed and sent to earth. So there is need for Super resolution of those compressed or noisy images. So, here we simply implement Super-resolution for Astronomical objects using back propagation algorithm to overcome lost information and challenges for high speedy celestial objects. The purpose is to super resolve high speedy celestial objects whose analysis may in future help to prevent collisions of such celestial objects with earth and also avoid future solar system damage

关键词： Super resolution Astronomical observations back propagation algorithm Low resolution images Gradient descent function mean square error function Gaussian kernel Linear Kernel Blur Sigma factor sparse toeplitz matrix bicubic interpolation High resolution image

来源：评论

学校读者我要写书评

暂无评论

Fine tuning the parameters of back propagation algorithm for optimum learning performance 2

Fine tuning the parameters of back propagation algorithm for...

引用

2nd IEEE International Conference on Contemporary Computing and Informatics (IC3I)

作者： Nagori, Viral GLS Univ Fac Comp Technol Ahmadabad Gujarat India

ISBN: (纸本)9781509052561

The back propagation algorithm has wide range of applications for training of feed forward neural networks. Over the years, many researchers have used back propagation algorithm to train their neural network based systems without emphasizing on how to fine tune the parameters of the algorithm. The paper throws the light on how researchers can manipulate and experiment with the parameters of the back propagation algorithm to achieve the optimum learning performance. The paper presents the results of the laboratory experiments of fine tuning the parameters of the back propagation algorithm. The process of fine tuning the parameters was applied on the neural network based expert system prototype. The prototype aims to analyze and design customized motivational strategies based on employees' perspective. The laboratory experiments were conducted on the following parameters of back propagation algorithm: learning rate, momentum rate and activation functions. Learning performance are measured and recorded. At the same time, the impact of activation function on the final output is also measured. Based on the results, the values of the above parameters which provide the optimum learning performance is chosen for the full scale system implementation.

关键词： back propagation algorithm neural network expert system motivational strategies learning performance activation function

来源：评论

学校读者我要写书评

暂无评论

Transient Stability Assessment and Parametric Study Using back propagation algorithm

引用

IFAC Proceedings Volumes 2000年第5期33卷 265-271页

作者： Toshihisa Funabashi Meidensha Corporation 36-2 Nihonbashi-Hakozakicho Chuo-Ku Tokyo 103-8515 Japan

This paper proposes a new method using back propagation algorithm and equal area criterion for fast transient stability assessment. The basic concept of the proposed method is shown for a one-machine with infinite-bus system. Then, examples of transient stability assessment are shown to demonstrate the powerfulness of the method in three categories, i.e., stability assessment, stability limits and parametric study. Finally, the example of stability limits calculation using back propagation algorithm is described in detail.

关键词： Transient stability Transient stability analysis Stability limits back propagation back propagation algorithm

来源：评论

学校读者我要写书评

暂无评论

PREDICTION OF FROSTING PROCESS ON COLD WALL SURFACE BASED ON ANN WITH back propagation algorithm

引用

THERMAL SCIENCE 2023年第5B期27卷 4135-4144页

作者： Sun, Jinjuan Ma, Zhiheng Tian, Jianhui Xian Technol Univ Sch Mechatron Engn Xian Peoples R China

The ANN with back propagation algorithm is a multi-layer feed-forward neural network, which is suitable to study unsteady frost formation with multiple factors. The back propagation ANN algorithm is used to study frost layer growth on cold flat surface, where four feature variables including temperature of cold flat sur-face, the velocity, relative humidity, and temperature of air are adopted. The frost growth experiment generates the database, which is good for training frost growth due to its fast speed and high precision based on Levenberg-Marquardt learning rule. The establishment of neural network model in this paper can quickly and accurately predict the frost layer height on cold flat surface of different control variables, which is helpful for the implementation of defrosting.

关键词： Key words: ANN back propagation algorithm ANN frosting process frosting characteristics frost height

来源：评论

学校读者我要写书评

暂无评论

Precision manufacturing technology and measurements in steel rolling industry using multi threshold fast fourier transform and back propagation algorithm for analysis of X-ray diffractometry

引用

Materials Today: Proceedings 2021年 38卷 2624-2628页

作者： K. Sujatha R.S. Ponmagal B. Deepalakshmi N. Jayachitra EEE Dept. Dr. MGR Educational and Research Institute Maduravoyal Chennai India Department of CSE SRM Institute of Science and Technology India Department of ECE Ramco Institute of Technology India Department of Chemical Engineering Dr. MGR Educational and Research Institute Maduravoyal Chennai India

X-ray diffractometry is a unique technique and that the X-ray diffraction patterns which depict the structure of the steel sheets during processing with the features extracted, that they serve directly as a signature which is very complicated. X-ray diffraction (XRD) techniques are a type of non-destructive method of investigation to identify the flaws during the fabrication of steel sheets. X-ray diffraction is comparatively simple and can be effectively used for the examination and identification of flaws during the rolling process of steel sheets. XRD technique finds application in various fields like textile industry, forensic, qualitative and quantitative phase analysis of poly crystalline material, to infer overall properties of the fiber and measure the degree of crystalline nature. It is extensively used to explore areas like material science, chemistry and in industry for research and quality control. This effective method gains novelty by combining the signal processing algorithms like multiple threshold based Fast Fourier Transform (FFT) and Artificial neural network (ANN) trained with back propagation algorithm (BPA) thereby offering an automated system for online monitoring during fabrication of flawless metal sheets. The hot rolled steel sheets for three categories namely, flawless, moderate flaw and extreme flaw conditions are obtained from the XRD pattern. Then multiple thresholds are incorporated to identify the peak position, peak width and peak intensity. The FFT algorithm computes the power spectrum which is used as features to identify the flaws in the steel sheets during cold rolling process. The extracted features are used as inputs to train the ANN with BPA whose performance is evaluated to be 90% efficient.

关键词： X-ray diffractometry Steel rolling Industry Multi-level threshold Fast fourier transform algorithm back propagation algorithm

来源：评论

学校读者我要写书评

暂无评论

Improving the accuracy of heart disease diagnosis with an augmented back propagation algorithm

引用

Journal of Chongqing University 2003年第1期2卷 31-34页

作者：颜红梅 College of Bioengineering Chongqing University Chongqing 400044 P.R. China

A multilayer perceptron neural network system is established to support the diagnosis for five most common heart diseases (coronary heart disease, rheumatic valvular heart disease, hypertension, chronic cor pulmonale and congenital heart disease). Momentum term, adaptive learning rate, the forgetting mechanics, and conjugate gradients method are introduced to improve the basic BP algorithm aiming to speed up the convergence of the BP algorithm and enhance the accuracy for diagnosis. A heart disease database consisting of 352 samples is applied to the training and testing courses of the system. The performance of the system is assessed by cross-validation method. It is found that as the basic BP algorithm is improved step by step, the convergence speed and the classification accuracy of the network are enhanced, and the system has great application prospect in supporting heart diseases diagnosis.

关键词： multilayer perceptron back propagation algorithm heart disease momentum term adaptive learning rate the forgetting mechanics conjugate gradients method

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：