Deep learning is a form of machine learning that enables computers to learn from experience and understand the world in terms of a hierarchy of concepts. Because the computer gathers knowledge from experience, there is no need for a human computer operator to formally specify all the knowledge that the computer needs. The hierarchy of concepts allows the computer to learn complicated concepts by building them out of simpler ones; a graph of these hierarchies would be many layers deep. This book introduces a broad range of topics in deep learning. The text offers mathematical and conceptual background, covering relevant concepts in linear algebra, probability theory and information theory, numerical computation, and machine learning. It describes deep learning techniques used by practitioners in industry, including deep feedforward networks, regularization, optimization algorithms, convolutional networks, sequence modeling, and practical methodology; and it surveys such applications as natural language processing, speech recognition, computer vision, online recommendation systems, bioinformatics, and videogames. Finally, the book offers research perspectives, covering such theoretical topics as linear factor models, autoencoders, representation learning, structured probabilistic models, Monte Carlo methods, the partition function, approximate inference, and deep generative models. Deep Learning can be used by undergraduate or graduate students planning careers in either industry or research, and by software engineers who want to begin using deep learning in their products or platforms. A website offers supplementary material for both readers and instructors.

Deep Learning

THE DESIGN AND ANALYSIS OF EXPERIMENTS. By Oscar Kempthorne. New York, John Wiley and Sons, Inc., 1952. 631 pp. $8.50. This book by a teacher of statistics (as well as a consultant for \"experimenters\") is a comprehensive study of the philosophical background for the statistical design of experiment. It is necessary to have some facility with algebraic notation and manipulation to be able to use the volume intelligently. The problems are presented from the theoretical point of view, without such practical examples as would be helpful for those not acquainted with mathematics. The mathematical justification for the techniques is given. As a somewhat advanced treatment of the design and analysis of experiments, this volume will be interesting and helpful for many who approach statistics theoretically as well as practically. With emphasis on the \"why,\" and with description given broadly, the author relates the subject matter to the general theory of statistics and to the general problem of experimental inference. MARGARET J. ROBERTSON

The Design and Analysis of Experiments

Computational geometry

The authors discuss high-voltage power conversion. Conventional series connection and three-level voltage source inverter techniques are reviewed and compared. A novel versatile multilevel commutation cell is introduced: it is shown that this topology is safer and more simple to control, and delivers purer output waveforms. The authors show how this technique can be applied to either choppers or voltage-source inverters and generalized to any number of switches.<<ETX>>

Multi-level conversion : high voltage choppers and voltage-source inverters

Nanotechnology is the science of understanding matter and the control of matter at dimensions of 100 nm or less. Encompassing nanoscale science, engineering, and technology, nanotechnology involves imaging, measuring, modeling, and manipulation of matter at this level of precision. An important aspect of research in nanotechnology involves precision control and manipulation of devices and materials at a nanoscale, i.e., nanopositioning. Nanopositioners are precision mechatronic systems designed to move objects over a small range with a resolution down to a fraction of an atomic diameter. The desired attributes of a nanopositioner are extremely high resolution, accuracy, stability, and fast response. The key to successful nanopositioning is accurate position sensing and feedback control of the motion. This paper presents an overview of nanopositioning technologies and devices emphasizing the key role of advanced control techniques in improving precision, accuracy, and speed of operation of these systems.

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A Survey of Control Issues in Nanopositioning

This paper reports the design and simulation results of a 433 MHz Power Amplifier (PA) which is designed in a 0.5 /spl mu/m CMOS technology and can provide variable gain modes. The PA consists of a driver and an output stage, and the gain is adjustable using digital codes. In this paper, 16.5 dB and 3.5 dB gain modes are chosen. This amplifier matches a 50 ohm load and provides 20 mW of output power at 432-434 MHz from a 3 V supply. The overall power efficiency is 30%.

The design of 433 MHz class AB CMOS power amplifier

Reduced metal-semiconductor contacts to sub 10 nm range have exhibited interesting characteristics that drastically deviate from those related to planar Schottky contacts. We present a theoretical model with analytical analyses that describe the crucial effect of the size of the metal contact, with a semiconductor substrate, on the energy band structure at the interface. We present a direct method for calculating the reduced depletion width, the enhanced built-in potential and enhanced electric field at the interface. The calculations showed that these parameters are direct functions of the radius of the nano metal particle when the substrate is moderately doped and this particle's radius effect diminishes when the sample is highly doped.

The significant effect of the size of a nano-metal particle on the interface with a semiconductor substrate

Electrocardiography (ECG) represents the hearts electrical activity and has features such as QRS complex, P-wave and T-wave that provide critical clinical information for detection and prediction of cardiac diseases. This paper presents a novel ECG processing architecture for the prediction of ventricular arrhythmia (VA). The architecture implements a novel ECG feature extraction which is optimized for ultra-low power applications. The architecture is based on Curve Length Transform (CLT) for the detection of QRS complex and Discrete Wavelet Transform (DWT) for the delineation of TP waves. Features extracted from two consecutive ECG cycles are used to set innovative parameters for VA prediction up to 3 hours before VA onset. Two databases of the heart signal recordings from the American Heart Association (AHA) and the MIT PhysioNet were used as training, test and validation sets to evaluate the performance of the proposed system.

A biomedical SoC architecture for predicting ventricular arrhythmia

Welcome to the Chip! Last year in the January issue of this magazine, the problem of simulating a sigma-delta modulator at the transistor level using SPICE was discussed and a simulation flow presented that could speed up simulation time significantly while keeping the accuracy almost intact. Transistor-level simulation is a must for optimizing the design at the final stages. In this column, we discuss a flow for the fast simulation of phase-lock loops, another widely used mixed-signal feedback system where transistor-level simulation is prohibitive. in the article, we discuss a mixed-mode methodology that uses macromodels for the digital parts while keeping the critical analog parts at the transistor level. We show that the method is effective and maintains very high accuracy.

A Methodology for Fast SPICE Simulation of Frequency Synthesizers

Robustness and yield enhancement techniques for RF circuits and systems are gaining accelerating traction due to increased PVT variability in nanometer CMOS. One of the more viable approaches that make use of the increasingly heterogeneous systems is digitally-assisted RF, enabling circuit programmability and flexibility. With the inclusion of the more robust digital, RF circuits' impairments may be successfully overcome or significantly diminished. This is enabled by implementing self-calibration mechanisms on top of self-test routines. In this paper, we highlight the basic requirements for enabling the on-chip self-calibration loop and discuss the main design steps. We also show an LNA circuit example demonstrating self-healing capabilities.

Mohammed Ismail

Papers

The design of 433 MHz class AB CMOS power amplifier

The significant effect of the size of a nano-metal particle on the interface with a semiconductor substrate

A biomedical SoC architecture for predicting ventricular arrhythmia

A Methodology for Fast SPICE Simulation of Frequency Synthesizers

Enabling efficient built-in-self-calibration for RFICs