這是LLE的原始算法，原文的參考文獻是：S.T.Roweis and L.K.Saul. Nonlinear dimensionality reduction by locally linear embedding. Science, 290, 2000.
上傳時間： 2013-12-20
上傳用戶：蟲蟲蟲蟲蟲蟲
This paper studies the problem of tracking a ballistic object in the reentry phase by processing radar measurements. A suitable (highly Nonlinear) model of target motion is developed and the theoretical Cramer—Rao lower bounds (CRLB) of estimation error are derived. The estimation performance (error mean and
標簽： processing ballistic the tracking
上傳時間： 2014-10-31
上傳用戶：yyyyyyyyyy
This paper studies the problem of tracking a ballistic object in the reentry phase by processing radar measurements. A suitable (highly Nonlinear) model of target motion is developed and the theoretical Cramer—Rao lower bounds (CRLB) of estimation error are derived. The estimation performance (error mean and
標簽： processing ballistic the tracking
上傳時間： 2014-01-14
上傳用戶：奇奇奔奔
This paper studies the problem of tracking a ballistic object in the reentry phase by processing radar measurements. A suitable (highly Nonlinear) model of target motion is developed and the theoretical Cramer—Rao lower bounds (CRLB) of estimation error are derived. The estimation performance (error mean and
標簽： processing ballistic the tracking
上傳時間： 2013-12-22
上傳用戶：asddsd
matlab 7.0 以上版本提供了強大的優化工具箱，但在整數規劃方面，只提供了bintprog（）這個m文件以求解0－1整數規劃，而對于一般的整數規劃模型沒有具體的算法提供。我們一般情況只是用最簡單的分值定界思想編寫matlab程序求解整數規劃問題，但效率低下，如何利用求解整數規劃的先進算法編寫matlab程序提上日程，香港大學的李端和復旦大學編寫的《Nonlinear Integer Programming》(非線性整數規劃)為編寫解決整數規劃問題提供強大有效的算法，其中算法針對具體問題包括： lagrangian 對偶問題 代理對偶問題 非線性lagrangian 和強對偶問題 非線性背包問題 可分解的整數規劃問題 二次目標函數的整數規劃問題 非約束的0－1多項式規劃問題 約束的 0－1多項式規劃問題 混合整數非線性規劃問題
上傳時間： 2017-02-27
上傳用戶：zhaoq123
This is a code of Pseudo-Arc Length Continuation Method , the method can be used for solving the Nonlinear equations, the principle can re found in some text books. In the code,I prove the agreement of the code with other methods
標簽： Continuation Pseudo-Arc the solving
上傳時間： 2013-12-03
上傳用戶：xzt
The book consists of three sections. The first, foundations, provides a tutorial overview of the principles underlying data mining algorithms and their application. The presentation emphasizes intuition rather than rigor. The second section, data mining algorithms, shows how algorithms are constructed to solve specific problems in a principled manner. The algorithms covered include trees and rules for classification and regression, association rules, belief networks, classical statistical models, Nonlinear models such as neural networks, and local memory-based models. The third section shows how all of the preceding analysis fits together when applied to real-world data mining problems. Topics include the role of metadata, how to handle missing data, and data preprocessing.
標簽： foundations The consists sections
上傳時間： 2017-06-22
上傳用戶：lps11188
Abstract—Stable direct and indirect decentralized adaptive radial basis neural network controllers are presented for a class of interconnected Nonlinear systems. The feedback and adaptation mechanisms for each subsystem depend only upon local measurements to provide asymptotic tracking of a reference trajectory. Due to the functional approximation capabilities of radial basis neural networks, the dynamics for each subsystem are not required to be linear in a set of unknown coeffi cients as is typically required in decentralized adaptive schemes. In addition, each subsystem is able to adaptively compensate for disturbances and interconnections with unknown bounds.
標簽： decentralized controllers Abstract adaptive
上傳時間： 2017-08-17
上傳用戶：gdgzhym
Computational models are commonly used in engineering design and scientific discovery activities for simulating complex physical systems in disciplines such as fluid mechanics, structural dynamics, heat transfer, Nonlinear structural mechanics, shock physics, and many others. These simulators can be an enormous aid to engineers who want to develop an understanding and/or predictive capability for complex behaviors typically observed in the corresponding physical systems. Simulators often serve as virtual prototypes, where a set of predefined system parameters, such as size or location dimensions and material properties, are adjusted to improve the performance of a system, as defined by one or more system performance objectives. Such optimization or tuning of the virtual prototype requires executing the simulator, evaluating performance objective(s), and adjusting the system parameters in an iterative, automated, and directed way. System performance objectives can be formulated, for example, to minimize weight, cost, or defects; to limit a critical temperature, stress, or vibration response; or to maximize performance, reliability, throughput, agility, or design robustness. In addition, one would often like to design computer experiments, run parameter studies, or perform uncertainty quantification (UQ). These approaches reveal how system performance changes as a design or uncertain input variable changes. Sampling methods are often used in uncertainty quantification to calculate a distribution on system performance measures, and to understand which uncertain inputs contribute most to the variance of the outputs. A primary goal for Dakota development is to provide engineers and other disciplinary scientists with a systematic and rapid means to obtain improved or optimal designs or understand sensitivity or uncertainty using simulationbased models. These capabilities generally lead to improved designs and system performance in earlier design stages, alleviating dependence on physical prototypes and testing, shortening design cycles, and reducing product development costs. In addition to providing this practical environment for answering system performance questions, the Dakota toolkit provides an extensible platform for the research and rapid prototyping of customized methods and meta-algorithms
標簽： Optimization and Uncertainty Quantification
上傳時間： 2016-04-08
上傳用戶：huhu123456
非線性控制英文書籍，對于控制有研究的同學可以參考此書的控制方法。
上傳時間： 2017-12-26
上傳用戶：hisllyero2
