Во многих областях естествознания важное место занимают задачи классификации (распознавания) тех или иных явлений.
В самых общих чертах задачу распознавания можно сформулировать следующим образом. Пусть известно, что рассматриваемый объект может находиться в одном из конечного числа состояний. Требуется по некоторой информации об этом объекте опре-делить, в каком состоянии находится объект.
К задачам распознавания относятся, например, задача об оценке масштабов оруденения в геологии, диагностика заболеваний в медицине, определение экономической перспективности районов в экономике, задача контроля правильности работы устройства в технике, прогнозирование свойств химических соединений в химии, задача построения автоматов, умевших различать звуковые сигналы, рукописные буквы, геометрические образы и т.д. <...>

В IX пятилетке в мелиоративное строительство намечается вложить 26,6 млрд.руб., сумму, вдвое превышающую вложения за все предыдущие годы. Темп прироста орошаемых земель, составивший в прошлом пятилетки 200-300 тыс.га в год; должен увеличиться до 600 тыс.га. Выполнение зтих планов требует своевременного обеспечения строительства проектно-ометной документацией и невозможно без значительного повышения производительности труда при проведении геологических, почвенных, гидрогеологических, инженерно-геологических и других видов инженерно-мелиоративных изысканий. <..>

Mathematical methods have been employed by a few geologists since the earliest days of the profession. For example, mining geologists and engineers have used samples to calculate tonnages and estimate ore tenor for centuries. As Fisher pointed out (1953, p. 3), Lyell’s subdivision of the Tertiary on the basis of the relative abundance of modern marine organisms is a statistical procedure. Sedimentary petrologists have regarded grain-size and shape measurements as important sources of sedimentological information since the beginning of the last century. The hybrid Earth sciences of geochemistry, geophysics, and geohydrology require a firm background in mathematics, although their procedures are primarily derived from the non-geological parent. Similarly, mineralogists and crystallographers utilize mathematical techniques derived from physical and analytical chemistry. <...>

Many contemporary problems faced by Earth sciences and society are complex, for example, climate change, disaster risk, energy and water security, and preservation of oceans. Studies of these challenges require an interdisciplinary approach and common knowledge. This book contributes to closing the gap between Earth science disciplines and assists in utilisation of the growing amount of data from observations and experiments using modern techniques on data assimilation and inversions developed within the same/another discipline or across the disciplines. <...>

This book is rather broad in that it covers many disciplines regarding both mathematical tools (algebra, calculus, statistics) and application areas (airborne, automotive, communication and standard signal processing and automatic control applications). The book covers all the theory an applied engineer or researcher can ask for: from algorithms with complete derivations, their properties to implementation aspects.

The technical world is changing very rapidly. In only 15 years, the power of personal computers has increased by a factor of nearly one-thousand. By all accounts, it will increase by another factor of one-thousand in the next 15 years. This tremendous power has changed the way science and engineering is done, and there is no better example of this than Digital Signal Processing. <...>

Рассмотрены математические методы, используемые для построения математических моделей информационных процессов и управления: теория множеств, теория графов, математическая логика и теория нечетких множеств. Приведено много примеров построения элементов математических моделей информационных процессов и управления.
Для студентов технических вузов, обучающихся по специальности “Автоматизированные системы обработки информации и управления”.

Digital Signal Processing (DSP) is concernedwith the theoretical and practical aspects of representing information bearing signals in digital form and with using computers or special purpose digital hardware either to extract that information or to transform the signals in useful ways. Areas where digital signal processing has made a significant impact include telecommunications, man-machine communications, computer engineering, multimedia applications, medical technology, radar and sonar, seismic data analysis, and remote sensing, to name just a few. <...>

Students learn in a number of ways and in a variety of settings. They learn through lectures, in informal study groups, or alone at their desks or in front of a computer terminal. Wherever the location, students learn most efficiently by solving problems, with frequent feedback from an instructor, following a worked-out problem as a model. Worked-out problems have a number of positive aspects. They can capture the essence of a key concept — often better than paragraphs of explanation. They provide methods for acquiring new knowledge and for evaluating its use. They provide a taste of real-life issues and demonstrate techniques for solving real problems. Most important, they encourage active participation in learning <...>