Xem 1-20 trên 22 kết quả Dimensional reduction
  • Appendix A: An Overview on Time Series Data Mining includes Introduction, Similarity Search in Time Series Data, Feature-based Dimensionality Reduction, Discretization, Other Time Series Data Mining Tasks, Conclusions.

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  • It is more than a century since Karl Pearson invented the concept of Principal Component Analysis (PCA). Nowadays, it is a very useful tool in data analysis in many fields. PCA is the technique of dimensionality reduction, which transforms data in the high-dimensional space to space of lower dimensions. The advantages of this subspace are numerous. First of all, the reduced dimension has the effect of retaining the most of the useful information while reducing noise and other undesirable artifacts. Secondly, the time and memory that used in data processing are smaller.

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  • Reduction of the singularities of codimension one singular foliations in dimension three By Felipe Cano Contents 0. Introduction 1. Blowing-up singular foliations 1.1. Adapted singular foliations 1.2. Permissible centers 1.3. Vertical invariants 1.4. First properties of presimple singularities 2. Global strategy 2.1. Reduction to presimple singularities. Statement 2.2. Good points. Bad points. Equi-reduction 2.3. Finiteness of bad points 2.4. The influency locus 2.5. The local control theorem 2.6. Destroying cycles 2.7. Global criteria of blowing-up 3. Local control 3.1.

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  • A three-dimensional macroporous Cu/SnO2 composite anode sheet prepared via a novel method was prepared via a novel method that is based on selective reduction of metal oxides at appropriate temperatures. SnO2 particles were imbedded on the Cu particles within the three-dimensionally interconnected Cu substrate.

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  • This is a reference book for those practicing or otherwise having an interest in design for manufacturability (DFM). DFM principles and guidelines are many; no one person should be expected to remember them all nor the detailed information, such as suggested dimensional tolerances, process limits, expected surface finish values, or other details, of each manufacturing process. It is expected that those involved will keep this book handy for reference when needed.

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  • This book addresses different aspects of the research field and a wide range of topics in speech signal processing, speech recognition and language processing. The chapters are divided in three different sections: Speech Signal Modeling, Speech Recognition and Applications. The chapters in the first section cover some essential topics in speech signal processing used for building speech recognition as well as for speech synthesis systems: speech feature enhancement, speech feature vector dimensionality reduction, segmentation of speech frames into phonetic segments. ...

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  • We establish an exact relation between self-avoiding branched polymers in D + 2 continuum dimensions and the hard-core continuum gas at negative activity in D dimensions. We review conjectures and results on critical exponents for D + 2 = 2, 3, 4 and show that they are corollaries of our result. We explain the connection (first proposed by Parisi and Sourlas) between branched polymers in D + 2 dimensions and the Yang-Lee edge singularity in D dimensions.

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  • Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành hóa học dành cho các bạn yêu hóa học tham khảo đề tài: ITemplate-free Synthesis of One-dimensional Cobalt Nanostructures by Hydrazine Reduction Route

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  • Tuyển tập các báo cáo nghiên cứu về lâm nghiệp được đăng trên tạp chí lâm nghiệp Original article đề tài:"Reduction of wood hygroscopicity and associated dimensional response by repeated humidity cycles"

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  • We initiate a study comparing effectiveness of the transformed spaces learned by recently proposed supervised, and semisupervised metric learning algorithms to those generated by previously proposed unsupervised dimensionality reduction methods (e.g., PCA). Through a variety of experiments on different realworld datasets, we find IDML-IT, a semisupervised metric learning algorithm to be the most effective.

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  • Six new benzopyran derivatives were synthesized by reduction reaction and Michael reaction from malloapelta B.

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  • Many classical integrable systems (like the Euler, Lagrange and Kowalewski tops or the Neumann system) as well as finite dimensional reductions of many integrable PDEs share the property of being algebraically completely integrable systems4. This means that they are completely integrable Hamiltonian systems in the usual sense and, moreover, their complexified invariant tori are open subsets of complex Abelian tori on which the complexified flow is linear. To such systems the powerful algebro-geometrical techniques may be applied...

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  • This book collects the lecture notes of two courses and one mini-course held in a winter school in Bologna in January 2005. The aim of this school was to popularize techniques of geometric measure theory among researchers and PhD students in hyperbolic differential equations. Though initially developed in the context of the calculus of variations, many of these techniques have proved to be quite powerful for the treatment of some hyperbolic problems.

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  • This paper presents a method for inducing the parts of speech of a language and partof-speech labels for individual words from a large text corpus. Vector representations for the part-of-speech of a word are formed from entries of its near lexical neighbors. A dimensionality reduction creates a space representing the syntactic categories of unambiguous words. A neural net trained on these spatial representations classifies individual contexts of occurrence of ambiguous words. The method classifies both ambiguous and unambiguous words correctly with high accuracy. ...

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  • Main Receive Aperture and Analog Beamforming Data to be Processed The Processing Needs and Major Issues Temporal DOF Reduction Adaptive Filtering with Needed and Sample-Supportable DOF and Embedded CFAR Processing 70.6 Scan-To-Scan Track-Before-Detect Processing 70.7 Real-Time Nonhomogeneity Detection and Sample Conditioning and Selection 70.8 Space or Space-Range Adaptive Pre-Suppression of Jammers 70.9 A STAP Example with a Revisit to Analog Beamforming 70.

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  • Distance, range number, bilaterial tolerance Width, range number Constant Helix diameter Dimensional operator Young's modulus Error using n applications of Simpson's rule The /th exponent Function The /th derivative of function / Fundamental dimension of force, fractional reduction of interval of uncertainty Function Function, ordinate spacing Index Second area moment, value of integral Approximate value of integral using i applications of Simpson's rule Spring rate

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  • CHAPTER 11 MINIMIZING ENGINEERING EFFORT Charles R. Mischke, Ph.D., P.E. Professor Emeritus of Mechanical Engineering Iowa State University Ames, Iowa 11.1 INTRODUCTION/11.2 11.2 REDUCING THE NUMBER OF EXPERIMENTS /11.3 11.3 SIMILITUDE/11.7 11.4 OPTIMALITY/11.9 11.5 QUADRATURE/11.13 11.6 CHECKING/11.15 REFERENCES/11.

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  • Tham khảo sách 'principal component analysis – engineering applications', kỹ thuật - công nghệ, cơ khí - chế tạo máy phục vụ nhu cầu học tập, nghiên cứu và làm việc hiệu quả

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  • The Fourier transform of a C ∞ function, f , with compact support on a real reductive Lie group G is given by a collection of operators φ(P, σ, λ) := π P (σ, λ)(f ) for a suitable family of representations of G, which depends on a family, indexed by P in a finite set of parabolic subgroups of G, of pairs of parameters (σ, λ), σ varying in a set of discrete series, λ lying in a complex finite dimensional vector space. The π P (σ, λ) are generalized principal series, induced from P . It is...

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  • One of the major problems of K-means is that one must use dense vectors for its centroids, and therefore it is infeasible to store such huge vectors in memory when the feature space is high-dimensional. We address this issue by using feature hashing (Weinberger et al., 2009), a dimension-reduction technique, which can reduce the size of dense vectors while retaining sparsity of sparse vectors.

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