Probability Distributions.- Linear Models for Regression.- Linear Models for Classification.- Neural Networks.- Kernel Methods.- Sparse Kernel Machines.- Graphical Models.- Mixture Models and EM.- Approximate Inference.- Sampling Methods.- Continuous Latent Variables.- Sequential Data.- Combining Models.

Pattern Recognition and Machine Learning

https://users.encs.concordia.ca/~ymzhang/publications/ARC32-2-98Zhang_pp.229-252.pdf

Bibliographical review on reconfigurable fault-tolerant control systems

This ebook is the first authorized digital version of Kernighan and Ritchie's 1988 classic, The C Programming Language (2nd Ed.). One of the best-selling programming books published in the last fifty years, "K&R" has been called everything from the "bible" to "a landmark in computer science" and it has influenced generations of programmers. Available now for all leading ebook platforms, this concise and beautifully written text is a "must-have" reference for every serious programmers digital library.

As modestly described by the authors in the Preface to the First Edition, this "is not an introductory programming manual; it assumes some familiarity with basic programming concepts like variables, assignment statements, loops, and functions. Nonetheless, a novice programmer should be able to read along and pick up the language, although access to a more knowledgeable colleague will help."

The C programming language

With advanced computer technology, systems are getting larger to fulfill more complicated tasks: however, they are also becoming less reliable. Consequently, testing is an indispensable part of system design and implementation; yet it has proved to be a formidable task for complex systems. This motivates the study of testing finite stare machines to ensure the correct functioning of systems and to discover aspects of their behavior. A finite state machine contains a finite number of states and produces outputs on state transitions after receiving inputs. Finite state machines are widely used to model systems in diverse areas, including sequential circuits, certain types of programs, and, more recently, communication protocols. In a testing problem we have a machine about which we lack some information; we would like to deduce this information by providing a sequence of inputs to the machine and observing the outputs produced. Because of its practical importance and theoretical interest, the problem of testing finite state machines has been studied in different areas and at various times. The earliest published literature on this topic dates back to the 1950's. Activities in the 1960's mid early 1970's were motivated mainly by automata theory and sequential circuit testing. The area seemed to have mostly died down until a few years ago when the testing problem was resurrected and is now being studied anew due to its applications to conformance testing of communication protocols. While some old problems which had been open for decades were resolved recently, new concepts and more intriguing problems from new applications emerge. We review the fundamental problems in testing finite state machines and techniques for solving these problems, tracing progress in the area from its inception to the present and the stare of the art. In addition, we discuss extensions of finite state machines and some other topics related to testing.

Principles and methods of testing finite state machines-a survey

Ultrathin films of single-walled carbon nanotubes (SWNTs) represent an attractive, emerging class of material, with properties that can approach the exceptional electrical, mechanical, and optical characteristics of individual SWNTs, in a format that, unlike isolated tubes, is readily suitable for scalable integration into devices. These features suggest the potential for realistic applications as conducting or semiconducting layers in diverse types of electronic, optoelectronic and sensor systems. This article reviews recent advances in assembly techniques for forming such films, modeling and experimental work that reveals their collective properties, and engineering aspects of implementation in sensors and in electronic devices and circuits with various levels of complexity. A concluding discussion provides some perspectives on possibilities for future work in fundamental and applied aspects.

http://www.ifc.dicp.ac.cn/library/cailiao/pdf1/11.pdf

Ultrathin Films of Single-Walled Carbon Nanotubes for Electronics and Sensors: A Review of Fundamental and Applied Aspects

A highly dependable embedded fault-tolerant memory architecture for high performance massively parallel computing applications and its dependability assurance techniques are proposed and discussed in this paper. The proposed fault tolerant memory provides two distinctive repair mechanisms: the permanent laser redundancy reconfiguration during the wafer probe stage in the factory to enhance its manufacturing yield and the dynamic BIST/BISD/BISR (built-in-self-test-diagnosis-repair)-based reconfiguration of the redundant resources in field to maintain high field reliability. The system reliability which is mainly determined by hardware configuration demanded by software and field reconfiguration/repair utilizing unused processor and memory modules is referred to as HW/SW Co-reliability. Various system configuration options in terms of parallel processing unit size and processor/memory intensity are also introduced and their HW/SW Co-reliability characteristics are discussed. A modeling and assurance technique for HW/SW Co-reliability with emphasis on the dependability assurance techniques based on combinatorial modeling suitable for the proposed memory design is developed and validated by extensive parametric simulations. Thereby, design and Implementation of memory-reliability-optimized and highly reliable fault-tolerant field reconfigurable massively parallel computing systems can be achieved.

Fault tolerant memory design for HW/SW co-reliability in massively parallel computing systems

This paper introduces the HSPICE macromodel of a racetrack memory (also commonly known as a domain-wall memory). MATLAB is used to generate the HSPICE code and different features of a perpendicular magnetic anisotropy (PMA) racetrack memory are evaluated. The proposed model simulates the write, the read and the shift operations of a racetrack memory. A good agreement between the simulation results obtained from the proposed model and experimental data is achieved.

HSPICE macromodel of a PMA racetrack memory

On the Methods to Detect Sector Faults of a Disk Subsystem

In this letter, yttrium-iron-garnet (YIG) nanowires are synthesized in a porous silicon template via a sol-gel method; ferromagnetic resonance (FMR) and vibrating sample magnetometer (VSM) techniques are then utilized to investigate the magnetic properties of the YIG nanowires. Moreover, the effects of the annealing temperature on the saturation magnetization ${\text{4}\pi}M_{S}$ and the crystal phase of the ceramic wires are assessed. For annealing temperatures above the crystallization temperature (∼710 °C), ${\text{4}\pi}M_{S}$ is dramatically increased. Therefore, the ceramic wires are then routinely annealed at 800 °C for 2 hours. Based on the VSM measurements, the net saturation magnetization and the loading factor of the nanowires are found to be 85 G and 35% respectively. Using the FMR technique, a DC magnetic field is applied either perpendicular or parallel to the wire axis to obtain the anisotropy field from the FMR resonance conditions. It is confirmed that the anisotropy field is uniaxial and is equal to 398 Oe.

Ferromagnetic Resonance of Y 3 Fe 5 O 12 Nanowires

Approximate computing is a paradigm for high performance and low power design by compromising computational accuracy. In this paper, the structure of an approximate modified radix-4 Booth multiplier is analyzed. A probabilistic error model is proposed to facilitate the evaluation of the approximate multiplier for errors from the approximate radix-4 Booth encoding, the approximate regular partial product array, and the approximate 4--2 compressor. The normalized mean error distances (NMEDs) of 8-bit and 16-bit approximate designs are found by utilizing the proposed model. The results from the error model and the corresponding analytical framework are close to those found by simulation, thus confirming the validity of the proposed approach.

Fabrizio Lombardi

Papers

Fault tolerant memory design for HW/SW co-reliability in massively parallel computing systems

HSPICE macromodel of a PMA racetrack memory

On the Methods to Detect Sector Faults of a Disk Subsystem

Ferromagnetic Resonance of Y 3 Fe 5 O 12 Nanowires

A Probabilistic Error Model and Framework for Approximate Booth Multipliers