Signal Processing for Cognitive Radios

К вашим услугам!Хотите установить или настроить приложения?Или вам нужно настроить резервное копирование данных?Нужна консультация?Наши специалисты дистанционно помогут решить эти и многие задачи — быстро и профессионально.В стоимость входит оказание одной услуги из списка ниже. Услуга предоставляется для компьютеров (Mac, Windows) и смартфонов (iOS, Android). Технические требованияКак это работает? Вы сами выбираете, как хотите получить консультации: по телефону или с помощью удаленного подключения к вашему устройству. Работаем ежедневно с 8 до 22:00 (по московскому времени). Выберите необходимую услугуВ стоимость услуги входит консультация по одному из вопросов, перечисленных ниже.Установка и настройка приложенийНастройка учетной записи для электронной почтыНастройка резервного копирования данныхУстановка, обновление и настройка прикладных приложенийНастройка системыДиагностика системы, поиск и устранение ошибок и неисправностейПроверка и обновление драйверов устройствНастройка подключения к интернетуУстановка необходимых обновлений и системного программного обеспеченияНастройка и оптимизация параметров автозагрузкиОптимизация работы устройства для повышения быстродействияКонсультации по настройкам и работе на устройствеБезопасностьДетальный анализ устройства на наличие угроз и вредоносных программПроверка и настройка параметров безопасности устройстваРекомендации по созданию и хранению безопасных паролейКонсультации по безопасной работе в интернетеТехнические требованияУслуга предоставляется в отношении одного устройства. Выберите удобный способ получения консультации: по телефону или с помощью удаленного подключения консультанта к устройству. На вашем устройстве должна использоваться одна из перечисленных операционных систем.MacOSПоддерживаются версии MacOS от 10.7 (Lion) и выше.10.15 (Catalina)10.14 (Mojave)10.13 (High Sierra)10.12 (Sierra)10.11 (El Capitan)10.10 (Yosemite)10.9 (Mavericks)10.8 (Mountain Lion)10.7 (Lion)iOSПоддерживаются версии iOS от 9.0 и вышеWindowsПоддерживаются версии Windows от XP (SP3) и выше (Vista, 7, 8, 8.1, 10).AndroidПоддерживаются версии Android от 4.0 и выше Для удалённого подключения вам будет необходимо установить программу TeamViewer и предоставить консультанту удаленный доступ к устройству на время оказания услуги. Установить TeamViewerПорядок оказания услугиУслуга оказывается при наличии стабильного подключения к интернету, минимальная скорость интернета для оказания услуги 512 кб/секДля удаленного подключения клиенту необходимо установить программу TeamViewer и предоставить консультанту удаленный доступ к устройству на период оказания услуги.Услуга оказывается с 8:00 до 22:00 ежедневно (по московскому времени)Услуга доступна для использования клиентом сразу после ее оплаты на сайте. Код доступа предоставляется по адресу электронной почты, указанной клиентом при оформлении заказа. Запросить повторную отправку кода можно по телефону 8 (495) 777-777-5 (для Москвы и МО) или 8 800 600-777-5 (звонок по России бесплатный).Срок действия Кода доступа — шесть месяцев с даты приобретения (оплаты). Возврат стоимости услуги после истечения срока действия кода доступа не осуществляется.Услуга считается оказанной клиенту с момента завершения консультирования. В течение одного часа по завершении клиенту направляется письмо по электронной почте, в ответе на которое он может оценить оказанную услугу либо сообщить о своем отказе считать услугу оказанной надлежащим образом. Если в течение суток от клиента не получены возражения, услуга считается оказанной в полном объеме.Клиент уведомлен и соглашается с тем, что консультанту на период сеанса посредством TeamViewer доступен вид экрана устройства клиента и что во избежание дальнейших споров консультант производит видеофиксацию сеанса.Клиент обязуется наблюдать за ходом сеанса в режиме реального времени и давать согласие на каждое действие, производимое консультантом на его устройстве. Клиент вправе прервать сеанс в любой момент, при этом, услуга все равно будет считаться оказанной.Исполнитель не несет ответственности за доставку писем клиенту на неработающие почтовые сервера, настройки спам-фильтров или неверно указанные адреса электронной почты.Услуга оказывается ООО «реСтор».

A comprehensive guide to learning technologies that unlock the value in big data Cognitive Computing provides detailed guidance toward building a new class of systems that learn from experience and derive insights to unlock the value of big data. This book helps technologists understand cognitive computing's underlying technologies, from knowledge representation techniques and natural language processing algorithms to dynamic learning approaches based on accumulated evidence, rather than reprogramming. Detailed case examples from the financial, healthcare, and manufacturing walk readers step-by-step through the design and testing of cognitive systems, and expert perspectives from organizations such as Cleveland Clinic, Memorial Sloan-Kettering, as well as commercial vendors that are creating solutions. These organizations provide insight into the real-world implementation of cognitive computing systems. The IBM Watson cognitive computing platform is described in a detailed chapter because of its significance in helping to define this emerging market. In addition, the book includes implementations of emerging projects from Qualcomm, Hitachi, Google and Amazon. Today's cognitive computing solutions build on established concepts from artificial intelligence, natural language processing, ontologies, and leverage advances in big data management and analytics. They foreshadow an intelligent infrastructure that enables a new generation of customer and context-aware smart applications in all industries. Cognitive Computing is a comprehensive guide to the subject, providing both the theoretical and practical guidance technologists need. Discover how cognitive computing evolved from promise to reality Learn the elements that make up a cognitive computing system Understand the groundbreaking hardware and software technologies behind cognitive computing Learn to evaluate your own application portfolio to find the best candidates for pilot projects Leverage cognitive computing capabilities to transform the organization Cognitive systems are rightly being hailed as the new era of computing. Learn how these technologies enable emerging firms to compete with entrenched giants, and forward-thinking established firms to disrupt their industries. Professionals who currently work with big data and analytics will see how cognitive computing builds on their foundation, and creates new opportunities. Cognitive Computing provides complete guidance to this new level of human-machine interaction.

A comprehensive guide to the theory and practice of signal enhancement and array signal processing, including matlab codes, exercises and instructor and solution manuals Systematically introduces the fundamental principles, theory and applications of signal enhancement and array signal processing in an accessible manner Offers an updated and relevant treatment of array signal processing with rigor and concision Features a companion website that includes presentation files with lecture notes, homework exercises, course projects, solution manuals, instructor manuals, and Matlab codes for the examples in the book

Electromagnetic wave scattering from randomly rough surfaces in the presence of scatterers is an active, interdisciplinary area of research with myriad practical applications in fields such as optics, acoustics, geoscience and remote sensing. In this book, the Method of Moments (MoM) is applied to compute the field scattered by scatterers such as canonical objects (cylinder or plate) or a randomly rough surface, and also by an object above or below a random rough surface. Since the problem is considered to be 2D, the integral equations (IEs) are scalar and only the TE (transverse electric) and TM (transverse magnetic) polarizations are addressed (no cross-polarizations occur). In Chapter 1, the MoM is applied to convert the IEs into a linear system, while Chapter 2 compares the MoM with the exact solution of the field scattered by a cylinder in free space, and with the Physical Optics (PO) approximation for the scattering from a plate in free space. Chapter 3 presents numerical results, obtained from the MoM, of the coherent and incoherent intensities scattered by a random rough surface and an object below a random rough surface. The final chapter presents the same results as in Chapter 3, but for an object above a random rough surface. In these last two chapters, the coupling between the two scatterers is also studied in detail by inverting the impedance matrix by blocks. Contents 1. Integral Equations for a Single Scatterer: Method of Moments and Rough Surfaces. 2. Validation of the Method of Moments for a Single Scatterer. 3. Scattering from Two Illuminated Scatterers. 4. Scattering from Two Scatterers Where Only One is Illuminated. Appendix. Matlab Codes. About the Authors Christophe Bourlier works at the IETR (Institut d’Electronique et de T?l?communications de Rennes) laboratory at Polytech Nantes (University of Nantes, France) as well as being a Researcher at the French National Center for Scientific Research (CNRS) on electromagnetic wave scattering from rough surfaces and objects for remote sensing applications and radar signatures. He is the author of more than 160 journal articles and conference papers. Nicolas Pinel is currently working as a Research Engineer at the IETR laboratory at Polytech Nantes and is about to join Alyotech Technologies in Rennes, France. His research interests are in the areas of radar and optical remote sensing, scattering and propagation. In particular, he works on asymptotic methods of electromagnetic wave scattering from random rough surfaces and layers. Gildas Kubick? is in charge of the “Expertise in electroMagnetism and Computation” (EMC) laboratory at the DGA (Direction G?n?rale de l’Armement), French Ministry of Defense, where he works in the field of radar signatures and electromagnetic stealth. His research interests include electromagnetic scattering and radar cross-section modeling.

Cluster or co-cluster analyses are important tools in a variety of scientific areas. The introduction of this book presents a state of the art of already well-established, as well as more recent methods of co-clustering. The authors mainly deal with the two-mode partitioning under different approaches, but pay particular attention to a probabilistic approach. Chapter 1 concerns clustering in general and the model-based clustering in particular. The authors briefly review the classical clustering methods and focus on the mixture model. They present and discuss the use of different mixtures adapted to different types of data. The algorithms used are described and related works with different classical methods are presented and commented upon. This chapter is useful in tackling the problem of co-clustering under the mixture approach. Chapter 2 is devoted to the latent block model proposed in the mixture approach context. The authors discuss this model in detail and present its interest regarding co-clustering. Various algorithms are presented in a general context. Chapter 3 focuses on binary and categorical data. It presents, in detail, the appropriated latent block mixture models. Variants of these models and algorithms are presented and illustrated using examples. Chapter 4 focuses on contingency data. Mutual information, phi-squared and model-based co-clustering are studied. Models, algorithms and connections among different approaches are described and illustrated. Chapter 5 presents the case of continuous data. In the same way, the different approaches used in the previous chapters are extended to this situation. Contents 1. Cluster Analysis. 2. Model-Based Co-Clustering. 3. Co-Clustering of Binary and Categorical Data. 4. Co-Clustering of Contingency Tables. 5. Co-Clustering of Continuous Data. About the Authors G?rard Govaert is Professor at the University of Technology of Compi?gne, France. He is also a member of the CNRS Laboratory Heudiasyc (Heuristic and diagnostic of complex systems). His research interests include latent structure modeling, model selection, model-based cluster analysis, block clustering and statistical pattern recognition. He is one of the authors of the MIXMOD (MIXtureMODelling) software. Mohamed Nadif is Professor at the University of Paris-Descartes, France, where he is a member of LIPADE (Paris Descartes computer science laboratory) in the Mathematics and Computer Science department. His research interests include machine learning, data mining, model-based cluster analysis, co-clustering, factorization and data analysis. Cluster Analysis is an important tool in a variety of scientific areas. Chapter 1 briefly presents a state of the art of already well-established as well more recent methods. The hierarchical, partitioning and fuzzy approaches will be discussed amongst others. The authors review the difficulty of these classical methods in tackling the high dimensionality, sparsity and scalability. Chapter 2 discusses the interests of coclustering, presenting different approaches and defining a co-cluster. The authors focus on co-clustering as a simultaneous clustering and discuss the cases of binary, continuous and co-occurrence data. The criteria and algorithms are described and illustrated on simulated and real data. Chapter 3 considers co-clustering as a model-based co-clustering. A latent block model is defined for different kinds of data. The estimation of parameters and co-clustering is tackled under two approaches: maximum likelihood and classification maximum likelihood. Hard and soft algorithms are described and applied on simulated and real data. Chapter 4 considers co-clustering as a matrix approximation. The trifactorization approach is considered and algorithms based on update rules are described. Links with numerical and probabi