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检索条件"主题词=Back Propagation algorithm"

共 277 条记录，以下是171-180 订阅

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An Effective Estimation of Time-dependent Doppler Frequency for Weapon Fuzing

An Effective Estimation of Time-dependent Doppler Frequency ...

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IEEE Region 10 Conference (TENCON 2008)

作者： Chakravarti, Madhumita Chanda, Vijay Bhaskar Bandi, Jyothsna Chakravarti, Bhudeb Def Res & Dev Org Res Ctr Imarat Hyderabad 500069 Andhra Pradesh India Int Inst Informat Technol Hyderabad 500084 Andhra Pradesh India

ISBN: (纸本)9781424424085

Proximity sensing is required for a wide range of military applications, especially for weapon fuzing. In this paper, wavelet video processing is discussed which is used for proximity sensing of objects through their time dependent Doppler shift. A continuous wavelet transform is performed on the Doppler signal, after subjecting it to a time varying window, the signal features are extracted from resulting wavelet video. This is used as input to pattern recognition neural networks. The networks are trained to estimate the time varying Doppler shift from extracted features. When the Doppler shift reaches its optimum value the warhead will be initiated for optimum detonation.

关键词： Continuous Wavelet Transform Morlet wavelet feed forward Neural Network back propagation algorithm

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Real time fixed point adaptive chaotic system generator for deep brain stimulation using FPGA 16

Real time fixed point adaptive chaotic system generator for ...

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16th International Conference on Frontiers of Information Technology (FIT)

作者： Shah, Syed Aamir Ali Zhang, Lei Bais, Abdul Univ Regina Fac Engn & Appl Sci Regina SK Canada

ISBN: (纸本)9781538693551

Parkinson disease (PD) is a neurodegenerative disorder which is caused by the untimely death of dopamine generating neurons situated in substantia nigra pars compacta and striatum. The depletion of striatal dopamine induces the synchronization in brain activity in motor regions which results in tremors. Deep brain stimulation (DBS) is used as an obvious choice in therapy when the medication stops working. Traditional DBS systems are open loop systems in which stimulation parameters need to be adjusted manually from among a large pool of available combinations. This makes the whole process tedious for the doctors and traumatic for the patients. We have developed an FPGA based device which can monitor, learn and mimic the behavior of chaotic systems on the go. The purpose of this device is to learn the chaotic behavior of brain, when in normal state, and generate the chaotic stimulation signal during PD based tremors.

关键词： Chaotic system FPGA Fixed point implementation Parkinson disease Deep brain stimulation Artificial Neural Networks back propagation algorithm

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Feed Forward Neural Network Optimization using Self Adaptive Differential Evolution for Pattern Classification 1

Feed Forward Neural Network Optimization using Self Adaptive...

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IEEE International Conference on Recent Trends in Electronics, Information and Communication Technology (RTEICT)

作者： Bhatia, Shivani Vishwakarma, Virendra P. Guru Gobind Singh Indraprastha Univ Univ Sch Informat Technol Dept Comp Sci New Delhi India

ISBN: (纸本)9781509007745

In this paper, a multilayer perceptron feed forward neural network (MPFNN) with good self-adapting and generalization ability is presented. The network is mainly used for solving the complex problems based on classification as well as regression. Most commonly, back propagation (BP) algorithm is used to train MPFNN, which suffers from the problem of local minima, over-fitting and poor convergence. To overcome the aforementioned problem, self adaptive differential algorithm is used to optimize the weights and biases of the MPFNN in the proposed approach. The property of differential evolution (DE) of global search is used to find the optimum value of weights. The mutation factor and the crossover rate are adjusted in Self adaptive DE (SDE) to maintain exploring capability for different evolving phases. Training of MPFFNN with SDE gives better results as compared to training of MPFFNN with Genetic algorithm (GA) and DE. The experiments are performed over UCI datasets namely iris, glass, wine and ionosphere.

关键词： Differential evolution multilayer perceptron feed forward neural network (MPFNN) evolutionary algorithm back propagation algorithm

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Accurate Detection of Human Face Position in the Environmental Images using Gabor Wavelet Transformations

Accurate Detection of Human Face Position in the Environment...

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Computing Conference

作者： Ghods, Vahid Sohrabi, Mohammad Karim Joulaeian, Mehdi Islamic Azad Univ Semnan Branch Dept Elect & Comp Engn Semnan Iran

ISBN: (纸本)9781509054435

Face Detection means to determine the presence or absence as well as positions and range of all humans' faces in the image. In general, face detection methods can be decomposed into moving or stationary detections in color images or with gray levels. In this paper, a new approach is developed for face detection in stationary images with gray levels including a certain size, and maximum angle of 30 degrees and resistant against light variations in desirable time. The image features are extracted using Gabor wavelets algorithm and will be sent for testing into Perceptron Neural Network (PNN). In the training phase, 72 face images and 72 non-face images are used through the face-rec database. In addition, for each face or non-face image, its mirror image, rotated image with the angles of 5, 10 and 15 degrees in positive and negative directions and images with one pixel shift in all four directions are deployed within training set in order to reduce sensitivity of the network. Entirely, the results of simulation experiments demonstrated the effectiveness of the proposed method.

关键词： image processing artificial neural network back propagation algorithm Gabor wavelet transformation

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A Novel Approach to improve Efficiency in P2P Systems using backpropagation algorithm

A Novel Approach to improve Efficiency in P2P Systems using ...

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International Conference on Electrical, Electronics, and Optimization Techniques (ICEEOT)

作者： Ahmed, Mohd Sarfaraz Dulhare, Uma N. Hijab, Maniza MJCET Dept IT Banjara Hills Hyderabad Andhra Pradesh India Muffakham Jah Coll Engn & Technol Hyderabad Andhra Pradesh India

ISBN: (纸本)9781467399395

With the availability of large volumes of multimedia data in P2P file sharing systems, locating data needs to address a multi-modal retrieval. In this approach, the paper proposes to make use of indexing as a mechanism for organizing files and the use of distributional features for searching of a file using natural language text. Then it trains the nodes onto a P2P network using backpropagation algorithm and also make use of a heuristic search technique. Experimental results show improved efficiency in providing fast and accurate answers in P2P systems.

关键词： P2P systems back propagation algorithm Heuristic Search

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Image Retrieval Based on Color and Texture Feature Using Artificial Neural Network

Image Retrieval Based on Color and Texture Feature Using Art...

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2nd International Multi-Topic Conference

作者： Hussain, Sajjad Hashmani, Manzoor Moinuddin, Muhammad Yoshida, Mikio Kanjo, Hidenori IQRA Univ Fac Engn Sci & Technol Karachi Pakistan Broad Band Res Corp Osaka Japan

ISBN: (纸本)9783642289613

Content-based image retrieval CBIR is a technique that helps in searching a user desired information from a huge set of image files and interpret user intentions for the desired information. The retrieval of information is based on features of image like colour, shape, texture, annotation etc. Many of the existing methods focus on the feature extraction and to bridge up the gap between low level features and high level semantics. In this paper we propose a supervised machine learning (SML) using artificial neural network (ANN) and singular value decomposition (SVD) for image retrieval. Specifically we use back propagation algorithm (multilayer perceptron) (MLP) for training and testing our proposed model. Experimental results show that by changing parameters of feature vector back propagation method can have 62% precision instead of 49% as claimed by in Hyoung Ku LEE, Suk In Yoo [1].

关键词： Colour based image retrieval back propagation algorithm artificial neural network based image retrieval multilayer perceptron (MLP)

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Neural Network Controlled Gripper for Wire Bonding Machines in Semiconductor Fabrication

Neural Network Controlled Gripper for Wire Bonding Machines ...

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15th International Conference on Mechatronics and Machine Vision in Practice

作者： Baskaran, K. Savitha, R. Kulicke & Soffa Pte Ltd Singapore 554910 Singapore Nanyang Technol Univ Sch Elect & Elect Engn Aerosp Elect Lab Singapore Singapore

ISBN: (纸本)9781424437795

Extensive research focus is on the appropriate usage of neural networks in automation industry. This paper presents a neural network based approach for the wire-bonding machine in the semiconductor industry. The lead frame is the skeleton of the IC package, providing mechanical support to the die during its assembly into a finished product. It consists of a die paddle, to which the die is attached, and leads, which serve as the means for external electrical connection to the outside world. The die is connected to the leads by wires through wire bonding or by tape automated bonds. The wire bonding is a thermo-sonic (Thermal - Ultrasonic) process during which a series of die units in a lead frame are wire bonded with leads. Solenoid operated Index and Eject grippers are used for positioning the lead frame during this wire bonding. Electric current controls the force applied on the lead frame by the gripper. The current required for a force varies with the thickness of the lead frame. Extensive manual work is required in determining the current requirement for each thickness. We propose a neural network algorithm to determine this current for any thickness. The back propagation algorithm is used to train the network with the available data, so that the current requirement for any other thickness can be determined from the trained network.

关键词： Die paddle back propagation algorithm Gripper Solenoid wire bonding

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Comparison of BPA-MLP and LSTM-RNN for Stocks Prediction 6

Comparison of BPA-MLP and LSTM-RNN for Stocks Prediction

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6th International Symposium on Computational and Business Intelligence (ISCBI)

作者： Achkar, Roger Elias-Sleiman, Fady Ezzidine, Hasan Haidar, Nourhane Amer Univ Sci & Technol Dept Comp & Commun Engn Beirut Lebanon

ISBN: (纸本)9781538694503

Neural networks is considered one of the most developed concept in artificial intelligence, due to its ability to solve complex computational tasks, and its efficiency to find solutions. There is a wide range of applications that adopt this technique, one of which is in the financial investment issues. This paper presents an approach to predict stock market ratios using artificial neural networks. It considers two different techniques-BPA-MLP and LSTM-RNN-their potential, and their limitations. Tests were conducted on different data sets, such as Facebook (TM) stocks, Google (TM) stocks, and Bitcoin (TM) stocks. We achieve a best-case accuracy of 97% for MLP algorithm, and 99.5% for LSTM algorithm. While the results appear to be promising, a web interface is presented in order to accept a certain amount of money, and accordingly checks the best stock to invest in.

关键词： back propagation algorithm Multi-layer Perceptron Long Short-Term Memory Recurrent Neural Networks

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Intelligent Controller for Mobile Robot Based on Heuristic rule Base Network

Intelligent Controller for Mobile Robot Based on Heuristic r...

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7th International Conference on MEMS, NANO and Smart Systems (ICMENS 2011)

作者： Kumar, Singh Mukesh Kumar, Mishra Deepak Dayal, Parhi R. Prasad, Singh Mahendra Govt Engn Coll Dept Mech Engn Bilaspur CG India Ravishankar Inst Technol & Management Dept Mech Engn Raipur Madhya Pradesh India Natl Inst Technol Dept Mech Engn Rourkela Orissa India Priyadrashani Coll Eng Dept Mech Engn Nagpur Maharashtra India

ISBN: (纸本)9783037853122

This paper is related to the human perception based idea by using heuristic information for the navigation of mobile robots in cluttered dynamic environments which provides a general, robust, safe and optimized path. The heuristic rule base network consists of a simple algorithm which makes predefined estimation function very smaller. The estimation function should be adequately defined for desired movement in the environments. A navigation system using rule based technique that allows a mobile robot to travel in an environment about, which the robot has no prior knowledge. This heuristic rule is applied in conjunction with artificial neural network. The proposed intelligent controller provides an optimum trajectory which increases the effectiveness of a mobile robot. A series of simulations test has been conducted to show the effectiveness of the proposed algorithm.

关键词： Mobile robot rule base network back propagation algorithm

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Prediction of aging of battery for electric vehicles based on a modified version of neural networks 29

Prediction of aging of battery for electric vehicles based o...

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29th Mediterranean Conference on Control and Automation (MED)

作者： Hemdani, Jamila Soltani, Moez Telmoudi, Achraf Jabeur Chaari, Abdelkader Univ Tunis Natl Higher Engn Sch Tunis ENSIT Lab Ingn Syst Ind & Energies Renouvelables LISIER Tunis Tunisia

ISBN: (纸本)9781665422581

The battery is the key element to store and then supply electricity to the various components of Electric Vehicles (EV). However, the battery cannot be charged and discharged indefinitely. The main objective of this study is to develop a novel methodology for estimation of the ageing rate of a Lithium-Fer-Phosphate (LFP) battery used in electric vehicles in order to predict its Remaining Useful Life (RUL). Indeed, a new method based a modified version of neural networks is proposed. It is used to estimate the LFP battery's Discharge Capacity (DC) and to conclude about the battery's end of life.

关键词： Lithium-Fer-Phosphate batteries artificial neural networks electric vehicles back propagation algorithm discharge capacity remaining useful life

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