This book is intended to be a general introduction to neural networks for those with a computer architecture, circuits, or systems background. In the introduction (Chapter 1), we define key vo- cabulary, recap the history and evolution of the techniques, and for make the case for additional hardware support in the field.
標(biāo)簽： Deep_Learning_for_Computer_Archit ects
上傳時間： 2020-06-10
上傳用戶：shancjb
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.
標(biāo)簽： Deep-Learning-with-PyTorch
上傳時間： 2020-06-10
上傳用戶：shancjb
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.
標(biāo)簽： Foundations Science Data of
上傳時間： 2020-06-10
上傳用戶：shancjb
General paradigm in solving a computer vision problem is to represent a raw image using a more informative vector called feature vector and train a classifier on top of feature vectors collected from training set. From classification perspective, there are several off-the-shelf methods such as gradient boosting, random forest and support vector machines that are able to accurately model nonlinear decision boundaries. Hence, solving a computer vision problem mainly depends on the feature extraction algorithm
標(biāo)簽： Convolutional Networks Neural Guide to
上傳時間： 2020-06-10
上傳用戶：shancjb
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.
標(biāo)簽： Learning Machine IoT and
上傳時間： 2020-06-10
上傳用戶：shancjb
This edition of Digital Image Processing is a major revision of the book. As in the 1977 and 1987 editions by Gonzalez and Wintz, and the 1992, 2002, and 2008 editions by Gonzalez and Woods, this sixth-generation edition was prepared with students and instructors in mind. The principal objectives of the book continue to be to provide an introduction to basic concepts and methodologies applicable to digital image processing, and to develop a foundation that can be used as the basis for further study and research in this field. To achieve these objectives, we focused again on material that we believe is fundamental and whose scope of application is not limited to the solution of specialized problems. The mathematical complexity of the book remains at a level well within the grasp of college seniors and first-year graduate students who have introductory preparation in mathematical analysis, vectors, matrices, probability, statistics, linear systems, and computer programming. The book website provides tutorials to support readers needing a review of this background material
標(biāo)簽： Processing Digital Image
上傳時間： 2021-02-20
上傳用戶：
通信：不同的獨立系統(tǒng)利用線路互相交換數(shù)據(jù)便是通信。通信的主要目的是將數(shù)據(jù)從一端發(fā)送到另一端，以實現(xiàn)數(shù)據(jù)的交換。網(wǎng)絡(luò)：構(gòu)成整個通信的線路稱為網(wǎng)絡(luò)。計算機(jī)網(wǎng)絡(luò)：交換信息的系統(tǒng)若為計算機(jī)系統(tǒng)，則稱為計算機(jī)網(wǎng)絡(luò)（Computer Network）通信。發(fā)送端：就是根據(jù)協(xié)議將數(shù)據(jù)利用一定的程序通過線路發(fā)送出去。接收端：根據(jù)協(xié)議將數(shù)據(jù)收集起來并存儲或顯示在屏幕上
標(biāo)簽： 串行通信
上傳時間： 2021-11-30
上傳用戶：
uninstall the device in the "Computer Management" pannel.在設(shè)備管理器中卸載已有驅(qū)動install PL2303-Prolific_DriverInstaller_v1200安裝壓縮包中的PL2303-Prolific_DriverInstaller_v1200restart your computer.重啟計算機(jī)
上傳時間： 2022-03-13
上傳用戶：jiabin
M.NT68676.2A is a monitor control board, which is suitable for Asia-Pacific market. It can supportLED/LCD panels which resolution is up to 2048×1152.M.NT68676.2A can synchronize with computer automatically. Synchronization requires thesynchronous signal which horizontal and vertical sync are separated.M.NT68676.2A can support dynamic contrast control, headphone input and Digital volume controlsimultaneously.
標(biāo)簽： 樂華驅(qū)動板
上傳時間： 2022-03-13
上傳用戶：kent
本系統(tǒng)采用電動機(jī)電樞供電回路串接采樣電阻的方式來實現(xiàn)對小型直流有刷電動機(jī)的轉(zhuǎn)速測量。該系統(tǒng)主要由二階低通濾波電路,小信號放大電路、單片機(jī)測量顯示電路、開關(guān)穩(wěn)壓電源電路等組成。同時自制電機(jī)測速裝置,用高頻磁環(huán)作為載體,用線圈繞制磁環(huán),利用電磁感應(yīng)原理檢測電機(jī)運行時的漏磁,將變化的磁場信號轉(zhuǎn)化為磁環(huán)上的感應(yīng)電流。用信號處理單元電路將微弱電信號轉(zhuǎn)化為脈沖信號,送由單片機(jī)檢測,從而達(dá)到準(zhǔn)確測量電機(jī)的速度的要求。In this system, the sampling resistance of armature power supply circuit is connected in series to measure the speed of small DC brush motor. The system is mainly composed of second-order low-pass filter circuit, small signal amplifier circuit, single-chip measurement and display circuit, switching regulated power supply circuit and so on. At the same time, the self-made motor speed measuring device uses high frequency magnetic ring as the carrier, coil winding magnetic ring, and electromagnetic induction principle to detect the leakage of magnetic field during the operation of the motor, which converts the changed magnetic field signal into the induced current on the magnetic ring. The weak electric signal is transformed into pulse signal by signal processing unit circuit, which is sent to single chip computer for detection, so as to meet the requirement of accurate measurement of motor speed.
標(biāo)簽： 直流電動機(jī)
上傳時間： 2022-03-26
上傳用戶：
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