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  • Fundamentals_of_Global_Positioning_System1

    The purpose of this book is to present detailed fundamental information on a global positioning system (GPS) receiver. Although GPS receivers are popu- larly used in every-day life, their operation principles cannot be easily found in one book. Most other types of receivers process the input signals to obtain the necessary information easily, such as in amplitude modulation (AM) and frequency modulation (FM) radios. In a GPS receiver the signal is processed to obtain the required information, which in turn is used to calculate the user position. Therefore, at least two areas of discipline, receiver technology and navigation scheme, are employed in a GPS receiver. This book covers both areas.

    標簽: Fundamentals_of_Global_Positionin g_System_Receivers

    上傳時間: 2020-06-09

    上傳用戶:shancjb

  • Fundamentals_of_Global_Positioning_System2

    In this new edition of the book, only minor changes were made to the original nine chapters but three new chapters treat topics of increasing interest to GPS users and equipment developers. One topic, improving the GPS receiver sensi- tivity may extend their operations into buildings, which is becoming important for emergency rescue and urban warfare.

    標簽: Fundamentals_of_Global_Positionin g_System

    上傳時間: 2020-06-09

    上傳用戶:shancjb

  • Audio+Engineering

    Sound is simply an airborne version of vibration. The air which carries sound is a mixture of gases. In gases, the molecules contain so much energy that they break free from their neighbors and rush around at high speed. As Figure 1.1(a) shows, the innumerable elastic collisions of these high-speed molecules produce pressure on the walls of any gas container. If left undisturbed in a container at a constant temperature, eventually the pressure throughout would be constant and uniform.

    標簽: Engineering Audio

    上傳時間: 2020-06-09

    上傳用戶:shancjb

  • Practical Arduino Engineering

    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).

    標簽: Engineering Practical Arduino

    上傳時間: 2020-06-09

    上傳用戶:shancjb

  • Feedback Control Theory

    Striking developments have taken place since 1980 in feedback control theory. The subject has be- come both more rigorous and more applicable. The rigor is not for its own sake, but rather that even in an engineering discipline rigor can lead to clarity and to methodical solutions to problems. The applicability is a consequence both of new problem formulations and new mathematical solutions to these problems. Moreover, computers and software have changed the way engineering design is done. These developments suggest a fresh presentation of the subject, one that exploits these new developments while emphasizing their connection with classical control.

    標簽: Feedback Control Theory

    上傳時間: 2020-06-10

    上傳用戶:shancjb

  • Stable_adaptive_neural_network_control

    Recent years have seen a rapid development of neural network control tech- niques and their successful applications. Numerous simulation studies and actual industrial implementations show that artificial neural network is a good candidate for function approximation and control system design in solving the control problems of complex nonlinear systems in the presence of different kinds of uncertainties. Many control approaches/methods, reporting inventions and control applications within the fields of adaptive control, neural control and fuzzy systems, have been published in various books, journals and conference proceedings.

    標簽: Stable_adaptive_neural_network_co ntrol

    上傳時間: 2020-06-10

    上傳用戶:shancjb

  • Auto-Machine-Learning-Methods-Systems-Challenges

    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

    上傳時間: 2020-06-10

    上傳用戶: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.

    標簽: Embedded_Deep_Learning Algorithms

    上傳時間: 2020-06-10

    上傳用戶:shancjb

  • Embeddings in Natural Language Processing

    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

    上傳時間: 2020-06-10

    上傳用戶:shancjb

  • interpretable-machine-learning

    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.

    標簽: interpretable-machine-learning

    上傳時間: 2020-06-10

    上傳用戶:shancjb

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