This book was written by Michael Margolis with Nick Weldin to help you explore the amazing things you can do with Arduino. Arduino is a family of microcontrollers (tiny computers) and a software creation envi- ronment that makes it easy for you to create programs (called sketches) that can interact with the physical world. Things you make with Arduino can sense and respond to touch, sound, position, heat, and light. This type of technology, often referred to as physical computing, is used in all kinds of things, from the iPhone to automobile elec- tronics systems. Arduino makes it possible for anyone—even people with no program- ming or electronics experience—to use this rich and complex technology.
上傳時間： 2020-06-09
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There’s a story (it’s either an old vaudeville joke or a Zen koan) in which a fisherman asks a fish, “What’s the water like down there?” and the fish replies “What is water?” If the story is just a joke, the point is to make us laugh; but if it’s a koan, the point is that the most obvious and ubiquitous parts of our immediate environ- ment are, paradoxically, often the easiest to overlook.
標簽： Atmospheric Monitoring Arduino With
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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.
標簽： Observers Control Systems in
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Machine learning is a broad and fascinating field. Even today, machine learning technology runs a substantial part of your life, often without you knowing it. Any plausible approach to artifi- cial intelligence must involve learning, at some level, if for no other reason than it’s hard to call a system intelligent if it cannot learn. Machine learning is also fascinating in its own right for the philo- sophical questions it raises about what it means to learn and succeed at tasks.
標簽： Learning Machine Course in
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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.
標簽： Auto-Machine-Learning-Methods-Sys tems-Challenges
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Design for manufacturability and statistical design encompass a number of activities and areas of study spanning the integrated circuit design and manufacturing worlds. In the early days of the planar integrated circuit, it was typical for a handful of practitioners working on a particular design to have a fairly complete understanding of the manufacturing process, the resulting semiconductor active and passive devices, as well as the resulting circuit - often composed of as few as tens of devices. With the success of semiconductor scaling, predicted and - to a certain extent even driven - by Moore’s law, and the vastly increased complexity of modern nano-meter scale processes and the billion-device circuits they allow, there came a necessary separation between the various disciplines.
標簽： Manufacturability Statistical Design for and
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Artificial Intelligence (AI) has undoubtedly been one of the most important buz- zwords over the past years. The goal in AI is to design algorithms that transform com- puters into “intelligent” agents. By intelligence here we do not necessarily mean an extraordinary level of smartness shown by superhuman; it rather often involves very basic problems that humans solve very frequently in their day-to-day life. This can be as simple as recognizing faces in an image, driving a car, playing a board game, or reading (and understanding) an article in a newspaper. The intelligent behaviour ex- hibited by humans when “reading” is one of the main goals for a subfield of AI called Natural Language Processing (NLP). Natural language 1 is one of the most complex tools used by humans for a wide range of reasons, for instance to communicate with others, to express thoughts, feelings and ideas, to ask questions, or to give instruc- tions. Therefore, it is crucial for computers to possess the ability to use the same tool in order to effectively interact with humans.
標簽： Embeddings Processing Language Natural in
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PrefaceDuring the past years, there has been a quickly rising interest in radio access technologies for providingmobile as well as nomadic and fixed services for voice, video, and data. The difference indesign, implementation, and use between telecom and datacom technologies is also becoming moreblurred. One example is cellular technologies from the telecom world being used for broadband dataand wireless LAN from the datacom world being used for voice-over IP.Today, the most widespread radio access technology for mobile communication is digital cellular,with the number of users passing 5 billion by 2010, which is more than half of the world’s population.It has emerged from early deployments of an expensive voice service for a few car-borne users,to today’s widespread use of mobile-communication devices that provide a range of mobile servicesand often include camera, MP3 player, and PDA functions. With this widespread use and increasinginterest in mobile communication, a continuing evolution ahead is foreseen.This book describes LTE, developed in 3GPP (Third Generation Partnership Project) and providingtrue 4G broadband mobile access, starting from the first version in release 8 and through the continuingevolution to release 10, the latest version of LTE. Release 10, also known as LTE-Advanced,is of particular interest as it is the major technology approved by the ITU as fulfilling the IMTAdvancedrequirements. The description in this book is based on LTE release 10 and thus provides acomplete description of the LTE-Advanced radio access from the bottom up.Chapter 1 gives the background to LTE and its evolution, looking also at the different standardsbodies and organizations involved in the process of defining 4G. It also gives a discussion of the reasonsand driving forces behind the evolution.Chapters 2–6 provide a deeper insight into some of the technologies that are part of LTE and itsevolution. Because of its generic nature, these chapters can be used as a background not only for LTEas described in this book, but also for readers who want to understand the technology behind othersystems, such as WCDMA/HSPA, WiMAX, and CDMA2000.Chapters 7–17 constitute the main part of the book. As a start, an introductory technical overviewof LTE is given, where the most important technology components are introduced based onthe generic technologies described in previous chapters. The following chapters provide a detaileddescription of the protocol structure, the downlink and uplink transmission schemes, and the associatedmechanisms for scheduling, retransmission and interference handling. Broadcast operation andrelaying are also described. This is followed by a discussion of the spectrum flexibility and the associated
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