Algebra and Geometry (American Mathematical Society) | English | 2020 | ISBN-13 : 978-1470456764 | 417 pages | True PDF | 9.62 MB

This is the second of three volumes that, together, give an exposition of the mathematics of grades 9 12 that is simultaneously mathematically correct and grade-level appropriate. The volumes are consistent with CCSSM (Common Core State Standards for Mathematics) and aim at presenting the mathematics of K 12 as a totally transparent subject. The first part of this volume is devoted to the study of standard algebra topics: quadratic functions, graphs of equations of degree 2 in two variables, polynomials, exponentials and logarithms, complex numbers and the fundamental theorem of algebra, and the binomial theorem.

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"With respect to the ever-increasing developments in artificial intelligence and artificial neural network applications in different scopes such as medicine, industry, biology, history, military industries, recognition science, space, machine learning and etc., Neural Networks: History and Applications first discusses a comprehensive investigation of artificial neural networks. Next, the authors focus on studies carried out with the artificial neural network approach on the emotion recognition from 2D facial expressions between 2009 and 2019. The major objective of this study is to review, identify, evaluate and analyze the performance of artificial neural network models in emotion recognition applications. This compilation also proposes a simple nonlinear approach for dipole mode index prediction where past values of dipole mode index were used as inputs, and future values were predicted by artificial neural networks. The study was also conducted for seasonal dipole mode index prediction because the dipole mode index is more prominent in the Sep-Oct-Nov season. A subsequent study focuses on how mammography has a high false negative and false positive rate. As such, computer-aided diagnosis systems have been commercialized to help in micro-calcification detection and malignancy differentiation. Yet, little has been explored in differentiating breast cancers with artificial neural networks, one example of computer-aided diagnosis systems. The authors aim to bridge this gap in research. The penultimate chapter reviews the general conditions under which synaptic plasticity most effectively takes place to support the supervised learning of a precise temporal code. Then, the accuracy of each plasticity rule with respect to its temporal encoding precision is examined, and the maximum number of input patterns it can memorize using the precise timings of individual spikes as an indicator of storage capacity in different control and recognition tasks is explored. In closing, a case study is presented centered on an intelligent decision support system that is built on a neural network model based on the Encog machine learning framework to predict cryptocurrency close prices"--

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Used by hundreds of thousands of students since its first edition, INTRODUCTION TO PROBABILITY AND STATISTICS, 15th Edition, Metric Edition continues to blend the best of its proven, error-free coverage with new innovations. Written for the traditional Introductory Statistics course, the book takes advantage of modern technology--including computational software and graphing calculators--to facilitate statistical reasoning as well as the interpretation of statistical results.

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