multi concept in remote sensing
Signal Processing for Remote Sensing - Chapter 3 docx
... Testing The data used for training and testing the individual networks are obtained from multiple infrasound arrays located in different geographical regions with different geometries The six infrasound ... train and test the RBF NNs Of the 574 infrasound signals, 351 were used for training the remaining 223 were used for testing The criterion used to divide the data between the training and testing ... six neural modules, there is a single output neuron with hard-limiting binary values used during the training process (see Figure 3.2) After training, to determine whether a particular SOI belongs...
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Tài liệu A neural-network-based space-vector PWM controller for a three-level voltage-fed inverter induction motor drive doc
... Engineering Department, Bengal Engineering College, Calcutta, India, and received the Ph.D degree in electrical engineering from Indian Institute of Technology, Kharagpur, India, in 1987 and 1999, respectively ... (1–4), giving altogether 24 regions of In this paper, as indicated in Fig 3(a), mode is defined if the trajectory is within the inner hexagon, whereas mode is defined for operation outside the inner ... for neutral-point voltage balancing Fig shows the corresponding PWM waves of the three phases in all the four regions of sector Each switching pattern during is repeated inversely interval with...
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báo cáo hóa học:" Research Article Performance Analysis of Bit-Width Reduced Floating-Point Arithmetic Units in FPGAs: A Case Study of Neural Network-Based Face Detector" ppt
... floatingpoint multiplication unit is designed using a multiplier and a hard intellectual property (IP) core in an FPGA to improve speed Consequently, the multiplication was performed within cycles ... the input layer and the output layer Each layer contains a certain number of neurons The MLP is a neural network model that contains multiple layers, typically three or more layers including ... representation error increases with repetitive multiplication and addition in the neural network The difference in output can be expressed using the following equations with the notation depicted in Figure...
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Tài liệu A Backpropagation Neural Network for Computer Network Security doc
... 1997 Self-Organizing Maps Springler-Verlag, Berlin Sin, Y.L., W.L Low and P.Y Wong, 2002 Learning fingerprints for a database intrusion detection system Proc 7th Eur Symp Research in Computer Security, ... Data mining for network intrusion detection Proc NSF Workshop on Next Generation Data Mining Leonid, P., E Eskin and S.J Stolfo, 2001 Intrusion detection with unlabeled data using clustering Proc ... block chaining: In order to complicated decryption for illegal people, cipher block chaining can be used so that each plaintext block is XORed with the previous cipher block before being encrypted...
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Báo cáo khoa học: "Fast Semantic Extraction Using a Novel Neural Network Architecture" docx
... ASI Series • Incorporating known invariances via virtual training data In image recognition problems it is common to create artificial training data by taking into account invariances in the images, ... learning system to output semantic roles for syntactic constituents without using a time consuming parse tree Also, as explained before, we are interesting in exploring whether machine learning ... quadratic in time with respect to the number of training examples The number of support vectors involved in the SVM decision function also increases linearly with the number of training examples...
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neural network-based face detection
... of intensities in the window The histogram is computed for pixels inside an oval region in the window This compensates for differences in camera input gains, as well as improving contrast in ... However, collecting a “representative” set of non-faces is difficult Instead of collecting the images before training is started, the images are collected during training, in the following manner, ... not the window contains a face In the training set, 15 face examples are generated from each original image, by randomly rotating the images (about their center points) up to 10 , scaling between...
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rotation invariant neural network-based
... which not Instead of collecting the images before training is started, the images are collected during training in the following “bootstrap” manner, adapted from [Sung, 1996]: Create an initial ... match this distribution as closely as possible during training The positive examples used in training are already in upright positions During training, we can also run the scenery images from which ... step in processing a window of the input image is to apply the router network This network assumes that its input window contains a face, and is trained to estimate its orientation The inputs...
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experimental analysis of neural network based feature extractors for
... only 352 hand-printed characters in the training data set The number of cursive characters was increased from to 144, 304 and 599 Accordingly, the number of training characters increased from ... had 1,056 training pairs As can be seen from the above table, the classification rates increased when the number of training pairs increased Of course, since the number of training iterations ... classification rate for the training set decreased when the number of training pairs increased As the RMS error increased, the classification rates of the training set decreased, in this case, from 95.1%...
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neural network-based handwritten signature
... for HSV Training Individual Networks for Each Signer This scenario involved creating and training a single network for each individual, training using a randomly selected set of five genuine signatures ... training was done using three skilled forgeries Use of skilled forgeries in the training set results in a large improvement in error rates The OER using three skilled forgeries in training is ... approaches (including the classification error rates and timing results using different training algorithms and different compositions of the training set) In all experiments, five genuine signatures...
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neural network-based offline handwritten
... Signature artifacts occurring in the handwriting Also removed from consideration is the final trailing stroke in a signature in examination of the trailing strokes in different signatures produced ... of being invariant under image scaling, translation, rotation, and shear in which can be defined by following equations (Equation to 7), Hu’s Moment Invariant : Hu‘s introduced seven moment invariants ... little insight into the writer’s natural style, then no amount of modeling or analysis is going to result in a successful system Further, it is necessary to have multiple, meaningful features in...
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neural network based trajectory planning
... value obtained from inverse kinematic equations, hence the final value of the reference angles are obtained In the control loop, a PD controller is utilized to obtain good tracking in the joint space ... used for training the neural networks and the weights are updated according to (13) in order to minimize the cost function given in (14) neural network utilizing the information of error in the operational ... CONTROLLER The incremental changes to be made in the reference values of the joint angles to minimize the tip error in Cartesian coordinates are calculated in the neural networks as described in section...
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Báo cáo hóa học: " Research Article Validity-Guided Fuzzy Clustering Evaluation for Neural Network-Based Time-Frequency Reassignment" potx
... response and avoids overtraining Also, it helps in determining the optimal regularization parameters in an automated fashion [28] 3.2.1 Multiple Neural Networks Training and Selecting Localized Neural ... distant input patterns, causing training to slow down in attempting to represent input data that are significantly different [6] During the last decade there has been spectacular growth in the volume ... not overtrained For this, data pairs are grouped into separate training and validation sets The error is monitored on the validation set that does not take part in the training The training is stopped...
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báo cáo hóa học:" Research Article Analysis of the Effects of Finite Precision in Neural Network-Based Sound Classifiers for Digital Hearing Aids" pot
... set The training set is used to determine the weights of the MLP in the training process, the validation set helps evaluate progress during training and to determine when to stop training, and ... for improving speech intelligibility in hearing aids using a layered structure,” in Proceedings of the 7th International Conference Intelligent Data Engineering and Automated Learning (IDEAL ... following instructions: (1) copying x into one of the input register of the MAC unit, (2) copying the constant value of a into the other input register, (3) copying the result of this multiplication...
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Báo cáo hóa học: " Research Article Doubly Periodic Traveling Waves in a Cellular Neural Network with Linear Reaction" pdf
... all i ∈ Z, if, and only a − b sin 2ikπ ξ 2ikπ ξ 2ijπ ξ c − d sin 2ikπ ξ 3.10 2ijπ a − b cos − a ξ 2ηjπ sin ξ ξ 1 ξ sin 2ηkπ ξ c − d cos 2ikπ − c ξ 2ijπ b sin ξ d sin 2ikπ ξ By 3.3 and 3.5 , we ... called a traveling wave with velocity −δ/τ if vi t τ t vi δ , t ∈ N, i ∈ Z 2.9 In case δ and τ 1, our traveling wave is also called a standing wave Next, recall that a positive integer ω is called ... mutually distinct and n ≥ will be considered in a subsequent paper for the important reason that quite distinct techniques are needed Since the trivial polynomial is considered in , we may avoid...
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Báo cáo hóa học: " Neural-Network-Based Time-Delay Estimation Samir Shaltaf" docx
... the single input forms use input vectors with lengths equal to half of the input vector length for the parallel input form, hence resulting in a large reduction in the NN size In the training ... Shaltaf was born in Amman, Jordan, in 1962 He received his Ph.D degree in engineering, sensing, and signal processing, in 1992 from Michigan Technological University, Michigan, USA He joined Amman ... 1: NNs with three input mode schemes: (a) parallel input mode with 2N inputs, (b) difference input mode with N inputs, and (c) single input mode with N inputs The NN were trained with the filtered...
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neural network based adaptive controller design of robotic manipulators with an observer 88 doc
... multilayer NN modified dynamics function defined in (24), since the function is continuous with its bounded inputs Then tr satisfying (30) is defined in (8), is where is the apthe corresponding ... Tsinghua University, Beijing, China Now he is an Associate Professor in the Department of Computer Science and Technology, Tsinghua University, Beijing, China His research interests include intelligent ... (M’89) was born in Shanghai, China He received the B.S degree in physics/electrical engineering from Fudan University, Shanghai, China, in 1982 and the M.S degree in electrical engineering from Drexel...
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ARTIFICIAL NEURAL NETWORK BASED DSS FOR GAME ONLINE PUBLISHING IN VIETNAM
... game ArcheAge • • Cấu hình đề nghị: Hệ điều hành: 32-bit 64-Bit Windows XP SP3, Vista SP1, Win7 SP1, Win8/8.1 • • • • Vi xử lý: Intel Core i5 Đồ họa: nVidia GTS250 1GB Radeon HD 4850 1GB Bộ nhớ ... hôn, sinh hoạt • Tương tác người chơi, môi trường… Cốt truyện Kiếm hiệp, tiên hiệp, võ hiệp, manga, anime… Ví dụ: Naruto Online Thu phí • Free to play or Pay to play? • Free to play = Pay to win ... Game có hỗ trợ tính offline không? Cộng đồng Hệ thống tương tác fanpage – diễn đàn Các hoạt động tương tác trực tiếp: thi đấu, offline… Nhà phát hành Thu thập liệu Từ trang tin game tiếng : playpark.vn,...
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Electricity price time series forecasting in deregulated markets using recurrent neural network based approaches
... Learning – In Reinforcement learning, which is closely related 32 to dynamic programming, the learning of an input-output mapping is performed through continued interaction with the environment in ... novel learning algorithm for RNN training incorporating invariant measures of time series • Development of a multi- scale neural network models and their learning algorithm employing singular perturbation ... generators with higher marginal costs enter into the system Such seasonal factors have been studied in Ref [9-10] Since increases in demand push up prices, there are increasing incentives of even expensive...
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Artificial neural network based adaptive controller for DC motors
... more stable if an initial set of weights and biases is generated through the off-line trainings A combination of off-line and on-line training has been used in this study The initial set of weights ... and nonlinear systems by itself In order to cope with this difficulty, the intuitive and subjective thinking of the human mind was exploited, resulting in soft computing approaches that include ... discussed in Chapter four Next, the online training of the ANN with adaptive learning rate was discussed Finally, a better ANN structure, obtained by introducing a feedback loop within the ANN...
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Neural network based multiuser detectors for DS CDMA
... signal only in the i th time interval Synchronous systems find applications in multicast networks which require point (central station)-to-multipoint communications [22] as well as in uplink mobile ... implementation since the complexity of the detector increases exponentially with the increase in the number of users Therefore most of the research thereafter has focused on finding sub-optimum multiuser ... channel Whereas in conventional single user detection, the other user’s signals are treated as white noise, in multi- user detection, the signal information of multiple users such as spreading sequence,...
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