I wrote this book so that students, hobbyists, and engineers alike can take advantage of the Arduino platform by creating several projects that will teach them about the engineering process. I also wanted to guide the reader through introductory projects so that they could get a firm grasp on the Arduino Language, and how to incorporate several pieces of hardware to make their own projects. This book offers so much information on the Arduino, not just the basic LED projects but it offers different peripherals such as Ultrasonic sensor, the Xbox® controller, Bluetooth, and much more. This book also teaches the non-engineer to follow a process that will help them in future project (not just Arduino projects).
标签： Engineering Practical Arduino
上传时间： 2020-06-09
上传用户：shancjb
Control Systems Engineering is an exciting and challenging field and is a multidisciplinary subject. This book is designed and organized around the concepts of control systems engineering using MATLAB, as they have been developed in the frequency and time domain for an introductory undergraduate or graduate course in control systems for engineer- ing students of all disciplines.
上传时间： 2020-06-10
上传用户：shancjb
This reference design describes the design of a 3-phase AC induction vector control drive with position encoder coupled to the motor shaft. It is based on Motorola’s DSP56F805 dedicated motor control device. AC induction motors, which contain a cage, are very popular in variable speed drives. they are simple, rugged, inexpensive and available at all power ratings. Progress in the field of power electronics and microelectronics enables the application of induction motors for high-performance drives, where traditionally only DC motors were applied. Thanks to sophisticated control methods, AC induction drives offer the same control capabilities as high performance four-quadrant DC drives.
标签： Reference Designer Manual Phase DRM 023 AC
上传时间： 2020-06-10
上传用户：shancjb
This book is an outgrowth of a course developed at Stanford University over the past five years. It is suitable as a self-contained textbook for second-level undergraduates or for first-level graduate students in almost every field that employs quantitative methods. As prerequisites, it is assumed that the student may have had a first course in differential equations and a first course in linear algebra or matrix analysis. These two subjects, however, are reviewed in Chapters 2 and 3, insofar as they are required for later developments.
标签： Introduction_to_Dynamic_Systems
上传时间： 2020-06-10
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The basic topic of this book is solving problems from system and control theory using convex optimization. We show that a wide variety of problems arising in system and control theory can be reduced to a handful of standard convex and quasiconvex optimization problems that involve matrix inequalities. For a few special cases there are “analytic solutions” to these problems, but our main point is that they can be solved numerically in all cases. These standard problems can be solved in polynomial- time (by, e.g., the ellipsoid algorithm of Shor, Nemirovskii, and Yudin), and so are tractable, at least in a theoretical sense. Recently developed interior-point methods for these standard problems have been found to be extremely efficient in practice. Therefore, we consider the original problems from system and control theory as solved.
标签： Linear_Matrix_Inequalities_in_Sys tem
上传时间： 2020-06-10
上传用户：shancjb
Control systems are used to regulate an enormous variety of machines, products, and processes. they control quantities such as motion, temperature, heat flow, fluid flow, fluid pressure, tension, voltage, and current. Most concepts in control theory are based on having sensors to measure the quantity under control. In fact, control theory is often taught assuming the availability of near-perfect feedback signals. Unfortunately, such an assumption is often invalid. Physical sensors have shortcomings that can degrade a control system.
标签： Observers Control Systems in
上传时间： 2020-06-10
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The past decade has seen an explosion of machine learning research and appli- cations; especially, deep learning methods have enabled key advances in many applicationdomains,suchas computervision,speechprocessing,andgameplaying. However, the performance of many machine learning methods is very sensitive to a plethora of design decisions, which constitutes a considerable barrier for new users. This is particularly true in the booming field of deep learning, where human engineers need to select the right neural architectures, training procedures, regularization methods, and hyperparameters of all of these components in order to make their networks do what they are supposed to do with sufficient performance. This process has to be repeated for every application. Even experts are often left with tedious episodes of trial and error until they identify a good set of choices for a particular dataset.
标签： Auto-Machine-Learning-Methods-Sys tems-Challenges
上传时间： 2020-06-10
上传用户：shancjb
In this book for the optimisation of assembly conveyor lines we are dealing with series part production featured by a medium complexity degree and a medium number of individual components and assembly technique alternatives. Modern production techniques for medium to large series products or mass production usually involve assembly conveyor lines. they still use hand labour more or less automated. The aim is to have monotonous and similar in type operations or such causing fatigue, stress and production traumas, gradually replaced by automated assembly cycles, means and techniques. This usually widely involves industrial robots and handlers. Higher productivity, lower cost and higher quality of assembled products are usually required.
上传时间： 2020-06-10
上传用户：shancjb
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.
标签： Bishop-Pattern-Recognition-and-Ma chine-Learning
上传时间： 2020-06-10
上传用户：shancjb
Recent work has shown that convolutional networks can be substantially deeper, more accurate, and efficient to train if they contain shorter connections between layers close to the input and those close to the output. In this paper, we embrace this observation and introduce the Dense Convo- lutional Network (DenseNet), which connects each layer to every other layer in a feed-forward fashion.
标签： Convolutional Connected Networks Densely
上传时间： 2020-06-10
上传用户：shancjb
