Training issues and learning algorithms for feedforward and recurrent neural networks
Training issues and learning algorithms for feedforward and recurrent neural networks
... 1 TRAINING ISSUES AND LEARNING ALGORITHMS FOR FEEDFORWARD AND RECURRENT NEURAL NETWORKS TEOH EU JIN B.Eng (Hons., 1st Class), NUS A THESIS SUBMITTED FOR THE DEGREE OF DOCTOR ... text and a reader, and the process of interpreting that text must take into account all three What then we mean in overall terms by Training Issues , Learning Algorithms and Feedforward and Recurrent ... Third and lastly, what is the difference between feedforward and recurrent neural networks, and how does neural structure influence the efficacy of the learning algorithm that is applied? When are recurrent...
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Báo cáo hóa học: "Research Article Sequential and Adaptive Learning Algorithms for M-Estimation" ppt
... published works include robust LMStype algorithms [11–13] Bayesian learning has been a powerful tool for developing sequential learning algorithms The problem is formulated as a maximum a posteriori ... response and the scaling factor thus constitute an LMS-type algorithm with an adaptive step size A major contribution of this work is thus the development of new sequential and adaptive learning algorithms ... with an adaptive step size It is well established that a learning algorithm with adaptive step size usually outperforms those with fixed step size in terms of faster initial learning rate and lower...
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Optimization and learning algorithms for orthogonal frequency division multiplexing based dynamic spectrum access
... presented for (i) optimization algorithms for DSA, and (ii) learning algorithms for DSA INTRODUCTION 1.4.1 Optimization algorithms for DSA In centralized DSA, there is a need for an optimization ... 1.3 Orthogonal frequency division multiplexingbased CR A CR requires a flexible and adaptive physical layer in order to efficiently perform its required tasks Orthogonal frequency division multiplexing ... inefficient use of spectrum, and it is actually a cause of the spectrum scarcity Dynamic spectrum access (DSA) targets to im- INTRODUCTION Dynamic Spectrum Access Dynamic exclusive use model Spectrum commons...
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Báo cáo hóa học: " Improvement for detection of microcalcifications through clustering algorithms and artificial neural networks" ppt
... Cite this article as: Quintanilla-Domínguez et al.: Improvement for detection of microcalcifications through clustering algorithms and artificial neural networks EURASIP Journal on Advances in Signal ... paper, partitional clustering algorithms are considered for image segmentation, because of the great similarity between segmentation and clustering, although clustering was developed for feature space, ... Number of patterns assigned to MCs and NT Class Number of patterns by k-means 652,965 652,716 MCs 2,395 Table Number of patterns used for training and testing for each classifier Number of patterns...
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Báo cáo hóa học: " Research Article NML Computation Algorithms for Tree-Structured Multinomial Bayesian Networks" ppt
... 22: end for 23: Compute C(M(G), n) = i∈ch(∅) Ci (M(G), n) 24: Outpute PNML (xn | M(G)) = P(xn | M(G))/C(M(G), n) Algorithm 3: The algorithm for computing PNML (xn | M(G)) for a Bayesian forest ... See [16] for more details NML FOR BAYESIAN FORESTS The naive Bayes model discussed in the previous section has been successfully applied in various domains In this section we consider, tree-structured ... and the information-theoretic approach of this paper cannot be considered Bayesian The problem of computing NML for discrete data has been studied before In [15] a linear-time algorithm for the...
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Báo cáo hóa học: " Research Article Extended LaSalle’s Invariance Principle for Full-Range Cellular Neural Networks" pdf
... consequence of the generalized version of LaSalle’s invariance principle in this paper (3) The derivative Dφ in Definition and the extended version of LaSalle’s invariance principle in Theorem have been ... is a direct consequence of the extended version of LaSalle’s invariance principle in this paper The proof of [11, Theorem 1], which is not based on an invariance principle, is comparatively more ... fundamental properties of the solutions of FR-CNNs The extended LaSalle’s invariance principle for FR-CNNs and the convergence results for FR-CNNs are described in Sections and 5, respectively...
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New exponential stabilization criteria for non autonomous delayed neural networks via Riccati equations
... present some new sufficient conditions for exponential stabilization of non- autonomous neural networks system (2.1) Firstly, we consider the case delays functions satisfy condition (D1) For α > 0, ... those in [10] Conclusions In this paper, the problem of exponential stabilization for a class of non- autonomous neural networks with interval non- differentiable time-varying delays has been studied ... strictly less than one In this paper, we consider the problem of exponential stabilization for a class of nonautonomous cellular neural networks with time-varying delays The system under consideration...
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Báo cáo khoa học: "Fast Online Training with Frequency-Adaptive Learning Rates for Chinese Word Segmentation and New Word Detection" docx
... purpose fast online training method, ADF The proposed training method requires only a few passes to complete the training • We propose a joint model for Chinese word segmentation and new word detection ... features + New word detection + ADF training (replacing SGD training) The results are shown in Table 259 As we can see, the new features improved performance on both word segmentation and new word ... aiming to improve both segmentation and new word detection: detected new words are added to the word list lexicon in order to improve segmentation Based on our CRF word segmentation system, we...
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Báo cáo sinh học: "Efficient algorithms for training the parameters of hidden Markov models using stochastic expectation maximization (EM) training and Viterbi training" potx
... description of the two new algorithms for Viterbi training and stochastic EM training In addition, we implement all three algorithms, i.e the new algorithms for Viterbi training and stochastic EM training ... , Π s ( X )) and E i (y , L, M) = E iq (y , X , Π s ( X )) , Proof: The proof for this theorem is very similar to the proof of theorem for Viterbi training and therefore omitted The key differences ... for Viterbi training, Baum-Welch training and stochastic EM training for the three different models For each model, we implemented each of the three training methods using the linear-memory algorithms...
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The reality of teaching and learning reading for non-English majors at Banking Academy- Son Tay Training Center = Nghiên cứu thực trạng của việc dạy và học đọc
... FOR NON-ENGLISH MAJORS AT BANKING ACADEMY -SON TAY TRAINING CENTER ( Nghiên cứu thực trạng việc dạy học đọc hệ học tiếng Anh không chuyên Học viện Ngân hàng - Cơ sở đào tạo Sơn Tây ) M.A Minor Thesis ... conclusion, the purpose of the current study was to investigate the reality of teaching and learning reading English for non-English majors first- year at BA-STC To find out this reality, the observation, ... prepares them for what they are going to read, for creating expectations and stimulating their interest in the topic It enables them to bring something of their own to the reading of the text...
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Collaborative mobile learning systems for music education and training
... collaborative mobile learning of music It also discusses the philosophy, design, and development of two systems for music education to make mobile learning more usable for music educators and students ... designed, developed, and evaluated two m -learning systems: MOGCLASS (Musical mObile Group for Classroom Learning And Study in Schools) and MOGAT (MObile Games with Auditory Training) MOGCLASS focuses ... intelligibility and self-confidence Based on MOGCLASS and MOGAT, we proposed a collaborative mobile- learning technical framework for music education and training (in Chapter 1.3) MOGCLASS and MOGAT...
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