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Statistical-Learning-Theory

  • PID Controllers for Time-Delay Systems

    In this chapter we give a quick overview of control theory, explaining why integral feedback control works, describing PID controllers, and summariz- ing some of the currently available techniques for PID controller design. This background will serve to motivate our results on PID control, pre- sented in the subsequent chapters.

    标签: Controllers Time-Delay Systems PID for

    上传时间: 2020-06-10

    上传用户:shancjb

  • Deep Learning---1

    Inventors have long dreamed of creating machines that think. This desire dates back to at least the time of ancient Greece. The mythical figures Pygmalion, Daedalus, and Hephaestus may all be interpreted as legendary inventors, and Galatea, Talos, and Pandora may all be regarded as artificial life ( , Ovid and Martin 2004 Sparkes 1996 Tandy 1997 ; , ; , ).

    标签: Learning Deep

    上传时间: 2020-06-10

    上传用户:shancjb

  • Deep-Learning-with-PyTorch

    We’re living through exciting times. The landscape of what computers can do is changing by the week. Tasks that only a few years ago were thought to require higher cognition are getting solved by machines at near-superhuman levels of per- formance. Tasks such as describing a photographic image with a sentence in idiom- atic English, playing complex strategy game, and diagnosing a tumor from a radiological scan are all approachable now by a computer. Even more impressively, computers acquire the ability to solve such tasks through examples, rather than human-encoded of handcrafted rules.

    标签: Deep-Learning-with-PyTorch

    上传时间: 2020-06-10

    上传用户:shancjb

  • eisenstein-nlp-notes

    The goal of this text is focus on a core subset of the natural language processing, unified by the concepts of learning and search. A remarkable number of problems in natural language processing can be solved by a compact set of methods:

    标签: eisenstein-nlp-notes

    上传时间: 2020-06-10

    上传用户:shancjb

  • Embedded_Deep_Learning_-_Algorithms

    Although state of the art in many typical machine learning tasks, deep learning algorithmsareverycostly interms ofenergyconsumption,duetotheirlargeamount of required computations and huge model sizes. Because of this, deep learning applications on battery-constrained wearables have only been possible through wireless connections with a resourceful cloud. This setup has several drawbacks. First, there are privacy concerns. Cloud computing requires users to share their raw data—images, video, locations, speech—with a remote system. Most users are not willing to do this. Second, the cloud-setup requires users to be connected all the time, which is unfeasible given current cellular coverage. Furthermore, real-time applications require low latency connections, which cannot be guaranteed using the current communication infrastructure. Finally, wireless connections are very inefficient—requiringtoo much energyper transferredbit for real-time data transfer on energy-constrained platforms.

    标签: Embedded_Deep_Learning Algorithms

    上传时间: 2020-06-10

    上传用户:shancjb

  • Foundations of Data Science

    Computer science as an academic discipline began in the 1960’s. Emphasis was on programming languages, compilers, operating systems, and the mathematical theory that supported these areas. Courses in theoretical computer science covered finite automata, regular expressions, context-free languages, and computability. In the 1970’s, the study of algorithms was added as an important component of theory. The emphasis was on making computers useful. Today, a fundamental change is taking place and the focus is more on a wealth of applications. There are many reasons for this change. The merging of computing and communications has played an important role. The enhanced ability to observe, collect, and store data in the natural sciences, in commerce, and in other fields calls for a change in our understanding of data and how to handle it in the modern setting. The emergence of the web and social networks as central aspects of daily life presents both opportunities and challenges for theory.

    标签: Foundations Science Data of

    上传时间: 2020-06-10

    上传用户:shancjb

  • Intelligence_-A-Modern-Approach

    Artificial Intelligence (AI) is a big field, and this is a big book. We have tried to explore the full breadth of the field, which encompasses logic, probability, and continuous mathematics; perception, reasoning, learning, and action; and everything from microelectronic devices to robotic planetary explorers. The book is also big because we go into some depth. The subtitle of this book is “A Modern Approach.” The intended meaning of this rather empty phrase is that we have tried to synthesize what is now known into a common frame- work, rather than trying to explain each subfield of AI in its own historical context. We apologize to those whose subfields are, as a result, less recognizable.

    标签: A-Modern-Approach Intelligence

    上传时间: 2020-06-10

    上传用户:shancjb

  • Machine Learning and IoT

    The present era of research and development is all about interdisciplinary studies attempting to better comprehend and model our understanding of this vast universe. The fields of biology and computer science are no exception. This book discusses some of the innumerable ways in which computational methods can be used to facilitate research in biology and medicine—from storing enormous amounts of biological data to solving complex biological problems and enhancing the treatment of various diseases.

    标签: Learning Machine IoT and

    上传时间: 2020-06-10

    上传用户:shancjb

  • bootstrap

    Bootstrap algorithm used to compute significance of a statistical measure performed on the array X

    标签: bootstrap

    上传时间: 2020-12-02

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  • Operational Ampifier Stability 运算放大器的稳定性

    Wherever possible the overall technique used for this series will be "definition by example" withgeneric formulae included for use in other applications. To make stability analysis easy we will usemore than one tool from our toolbox with data sheet information, tricks, rules-of-thumb, SPICESimulation, and real-world testing all accelerating our design of stable operational amplifier (op amp)circuits. These tools are specifically targeted at voltage feedback op amps with unity-gain bandwidths<20 MHz, although many of the techniques are applicable to any voltage feedback op amp. 20 MHz ischosen because as we increase to higher bandwidth circuits there are other major factors in closing theloop: such as parasitic capacitances on PCBs, parasitic inductances in capacitors, parasitic inductancesand capacitances in resistors, etc. Most of the rules-of-thumb and techniques were developed not justfrom theory but from the actual building of real-world circuits with op amps <20 MHz.

    标签: 运算放大器

    上传时间: 2021-11-01

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