The main aim of this book is to present a unified, systematic description of
basic and advanced problems, methods and algorithms of the modern con-
trol theory considered as a foundation for the design of computer control
and management systems. The scope of the book differs considerably from
the topics of classical traditional control theory mainly oriented to the
needs of automatic control of technical devices and technological proc-
esses. Taking into account a variety of new applications, the book presents
a compact and uniform description containing traditional analysis and op-
timization problems for control systems as well as control problems with
non-probabilistic models of uncertainty, problems of learning, intelligent,
knowledge-based and operation systems – important for applications in the
control of manufacturing processes, in the project management and in the
control of computer systems.
Signals convey information. Systems transform signals. This book introduces the mathe-
matical models used to design and understand both. It is intended for students interested
in developing a deep understanding of how to digitally create and manipulate signals to
measure and control the physical world and to enhance human experience and communi-
cation.
Pattern recognition has its origins in engineering, whereas machine learning grew
out of computer science. However, these activities can be viewed as two facets of
the same field, and together they have undergone substantial development over the
past ten years. In particular, Bayesian methods have grown from a specialist niche to
become mainstream, while graphical models have emerged as a general framework
for describing and applying probabilistic models. Also, the practical applicability of
Bayesian methods has been greatly enhanced through the development of a range of
approximate inference algorithms such as variational Bayes and expectation propa-
gation. Similarly, new models based on kernels have had significant impact on both
algorithms and applications.
Machinelearninghasgreatpotentialforimprovingproducts,processesandresearch.Butcomputers
usually do not explain their predictions which is a barrier to the adoption of machine learning.
This book is about making machine learning models and their decisions interpretable.
After exploring the concepts of interpretability, you will learn about simple, interpretable models
such as decision trees, decision rules and linear regression. Later chapters focus on general model-
agnosticmethodsforinterpretingblackboxmodelslikefeatureimportanceandaccumulatedlocal
effects and explaining individual predictions with Shapley values and LIME.
This Getting Started Guide is written for Maxwell beginners and experienced users who would like to quickly re familiarize themselves with the capabilities of MaxwelL.This guide leads you step-by-step through solving and analyzing the results of a rotational actuator magnetostatic problem with motion By following the steps in this guide, you will learn how to perform the following tasks Modify a models design parameters y Assign variables to a model's design parameters.Specify solution settings for a design Validate a designs setupRun a maxwell simulation v Plot the magnetic flux density vecto v Include motion in the simulation本《入門指南》是為希望快速重新熟悉MaxwelL功能的Maxwell初學(xué)者和有經(jīng)驗的用戶編寫的。本指南將引導(dǎo)您逐步解決和分析旋轉(zhuǎn)致動器靜運動問題的結(jié)果。按照本指南中的步驟，您將學(xué)習(xí)如何執(zhí)行以下任務(wù)。修改模型設(shè)計參數(shù)y將變量分配給模型的設(shè)計參數(shù)。指定設(shè)計的解決方案設(shè)置驗證設(shè)計設(shè)置運行maxwell模擬v繪制磁通密度vecto v在模擬中包含運動
以STC12C5A60S2單片機為控制核心,采用2.4G(JF24D)無線遙控模塊進(jìn)行無線發(fā)射與接收,設(shè)計了一種雙電機遙控船模控制系統(tǒng).該系統(tǒng)通過切換檔桿實現(xiàn)前進(jìn)后退,方向盤左右轉(zhuǎn)動、暫停按鈕等控制直流電機的正轉(zhuǎn)、反轉(zhuǎn)、暫停,使得電機驅(qū)動的遙控船模實現(xiàn)前進(jìn)后退、左右轉(zhuǎn)向、暫停等功能,有效解決了驅(qū)動功率小和船模之間相互干擾等問題,可廣泛應(yīng)用于遙控船模領(lǐng)域.Using STC12C5A60S2 single-chip microcomputer as the controller and 2.4 G(JF24D)wireless remote control module for wireless transmission and reception, a dual-motor remote control ship model control system is designed. The system realizes forward and backward by switching the gear lever. The steering wheel rotates left and right and the pause button controls the forward, reverse and pause of the dc motor. The remote controller of ship model driven by the motor realizes forward and backward, left and right steering, pause and other functions. The ship model control system can effectively solve the problems of small driving power and mutual interference between ship models, and can be widely used in the field of remote controller of ship model.
統(tǒng)計學(xué)習(xí)基礎(chǔ):數(shù)據(jù)挖掘、推理與預(yù)測介紹了這些領(lǐng)域的一些重要概念。盡管應(yīng)用的是統(tǒng)計學(xué)方法，但強調(diào)的是概念，而不是數(shù)學(xué)。許多例子附以彩圖。《統(tǒng)計學(xué)習(xí)基礎(chǔ):數(shù)據(jù)挖掘、推理與預(yù)測》內(nèi)容廣泛，從有指導(dǎo)的學(xué)習(xí)（預(yù)測）到無指導(dǎo)的學(xué)習(xí)，應(yīng)有盡有。包括神經(jīng)網(wǎng)絡(luò)、支持向量機、分類樹和提升等主題，是同類書籍中介紹得最全面的。計算和信息技術(shù)的飛速發(fā)展帶來了醫(yī)學(xué)、生物學(xué)、財經(jīng)和營銷等諸多領(lǐng)域的海量數(shù)據(jù)。理解這些數(shù)據(jù)是一種挑戰(zhàn)，這導(dǎo)致了統(tǒng)計學(xué)領(lǐng)域新工具的發(fā)展，并延伸到諸如數(shù)據(jù)挖掘、機器學(xué)習(xí)和生物信息學(xué)等新領(lǐng)域。許多工具都具有共同的基礎(chǔ)，但常常用不同的術(shù)語來表達(dá)。【內(nèi)容推薦】《統(tǒng)計學(xué)習(xí)基礎(chǔ):數(shù)據(jù)挖掘、推理與預(yù)測》試圖將學(xué)習(xí)領(lǐng)域中許多重要的新思想?yún)R集在一起，并且在統(tǒng)計學(xué)的框架下解釋它們。隨著計算機和信息時代的到來，統(tǒng)計問題的規(guī)模和復(fù)雜性都有了急劇增加。數(shù)據(jù)存儲、組織和檢索領(lǐng)域的挑戰(zhàn)導(dǎo)致一個新領(lǐng)域“數(shù)據(jù)挖掘”的產(chǎn)生。數(shù)據(jù)挖掘是一個多學(xué)科交叉領(lǐng)域，涉及數(shù)據(jù)庫技術(shù)、機器學(xué)習(xí)、統(tǒng)計學(xué)、神經(jīng)網(wǎng)絡(luò)、模式識別、知識庫、信息提取、高性能計算等諸多領(lǐng)域，并在工業(yè)、商務(wù)、財經(jīng)、通信、醫(yī)療衛(wèi)生、生物工程、科學(xué)等眾多行業(yè)得到了廣泛的應(yīng)用。【作者簡介】Trevor Hastie,Robert Tibshirani和Jerome Friedman都是斯坦福大學(xué)統(tǒng)計學(xué)教授，并在這個領(lǐng)域做出了杰出的貢獻(xiàn)。Hastie和Tibshirani提出了廣義和加法模型，并出版專著“Generalized Additive models”。Hastie的主要研究領(lǐng)域為：非參數(shù)回歸和分類、統(tǒng)計計算以及生物信息學(xué)、醫(yī)學(xué)和工業(yè)的特殊數(shù)據(jù)挖掘問題。他提出主曲線和主曲面的概念，并用S-PLUS編寫了大量統(tǒng)計建模軟件。Tibshirani的主要研究領(lǐng)域為：應(yīng)用統(tǒng)計學(xué)、生物統(tǒng)計學(xué)和機器學(xué)習(xí)。他提出了套索的概念，還是“An Introduction to the Bootstrap”一書的作者之一。Friedman是CART、MARS和投影尋蹤等數(shù)據(jù)挖掘工具的發(fā)明人之一。他不僅是位統(tǒng)計學(xué)家，而且是物理學(xué)家和計算機科學(xué)家，先后在物理學(xué)、計算機科學(xué)和統(tǒng)計學(xué)的一流雜志上表發(fā)論文80余篇。
Mathematical modeling has become an important part of the research and devclopment work in engineering and scicnce. Retaining a competitive edge requiresa fast path between ideas and prototypes, and in this regard mathematical modeling and simulation provide a valuable shortcut for understanding both qualitative and quantitative aspects of scientific and engineering design. To assist you in gaining this edge, COMSOL Multiphysics offers state-of-the art performance, being built from the ground up with a Java3D interface and C/C++ solvers.The Acoustics Module is an optional package that extends the COMSOL Multiphysicsmodcling cnvironment with customized user interfaces and functionality optimizcd for the analysis of acoustics. Like all modules in the COMSOL family, it provides a brary of prewritten ready-to-run models that make it quicker and casier to analyze disciplinc-specific problcms.
