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

This work presents arithmetic coding and its application to data compression for VLSI testing. The use of arithmetic codes for compression results in a codeword whose length is close to the optimal value as predicted by entropy in information theory. Previous techniques (such as those based on Huffman or Golomb coding) result in optimal codes for test data sets in which the probability model of the symbols satisfies specific requirements. We show that Huffman and Golomb codes result in large differences between entropy bound and sustained compression. We present compression results of arithmetic coding for circuits through a practical integer implementation of arithmetic coding/decoding and analyze its deviation from the entropy bound as well. A software implementation approach is proposed and studied in detail using industrial embedded DSP cores.

Compression of VLSI test data by arithmetic coding

The authors present the basic structure of a testable and repairable programmable logic array (PLA) and the design modifications which are required for a full diagnosis and yield enhancement. The testing process is fully analyzed, and the conditions for diagnosis are presented. It is proved that identification in the presence of multiple (crosspoint, stuck-at, and bridging) faults is possible with high coverage. The criteria which permit diagnosis are based on a hierarchical organization of the testing process; significant improvements over previous redundant structures can be achieved. This results in a compact structure with a homogeneous layout which has been evaluated with respect to area overhead for VLSI implementation. Simulation results for benchmark devices are presented. These suggest that an efficient repair of VLSI PLAs for yield enhancement can be achieved. >

Location and identification for single and multiple faults in testable redundant PLAs for yield enhancement

Cardiovascular disease (CVD) has become the leading cause of death worldwide. As a widely used method for diagnosing CVD, currently electrocardiogram (ECG) monitoring tends to be implemented in wearable devices. This paper presents the prototype an ECG delineation and arrhythmia classification (EDAC) system suitable for wearable ECG biosensors. The proposed EDAC system is intended to be implemented after the electrodes and the analog front-end circuit, and its aim is signal processing at a low hardware overhead. The system consists of a Delta-modulator-based analog-to-feature converter (AFC), a corresponding ECG detection/delineation/feature extraction algorithm (DDF), an automatic gain controller (AGC) block, and a patient-dependent linear kernel support vector machine (SVM) classifier. The AFC converts the input analog signal into digital data of the slope and slope variation of the input signal, which is then used for detecting QRS complexes, localizing the fiducial points, and extracting the feature vectors for each heartbeat in the DDF block. At the same time, the AGC sends out a gain control signal based on the detected QRS complex to adjust the gain of the front-end amplifier. Finally, the SVM block performs arrhythmia classification. The EDAC system performance is evaluated using the MIT-BIH arrhythmia database. The system achieves 0.88% (0.93%), 99.1% (99.1%), 87.0% (92.8%), 99.6% (99.5%), and 89.3% (92.9%) in F1 score, accuracy, sensitivity, specificity, and positive predictive values of the supraventricular ectopic beats (ventricular ectopic beats) versus normal heartbeats classification while maintaining a low power dissipation ( $1.66~\mu \text{W}$ at 1 kHz operating frequency in the front-end AFC block). The proposed system is attractive to future wearable long-term ECG monitoring biosensors.

A Near-Sensor ECG Delineation and Arrhythmia Classification System

This paper proposes an approach for testing a nanocrossbar switch; fault detection is considered in the presence of faulty switches and nets (of a permanent nature only) in the crossbar. To ensure detection, a one-to-one (onto) relationship in the setting (programming) of the switches is established in each of the configurations of the crossbar. This is accomplished using a constant-sum transformation of the characteristic matrix of the crossbar by utilizing different graph algorithms in O(N4.5) where N is the matrix dimension. Matrix properties are related to graph algorithms to generate permutation matrices as corresponding to the configurations (phases) of the crossbar. The conditions by which multiple faults are detected by the modified counting sequence (as test set), are proved. Simulation results are provided to further substantiate the validity of the proposed approach to test nanocrossbars of very large dimension and with different switch distribution.

Testing a Nanocrossbar for Multiple Fault Detection

This paper presents an approach for the fault-tolerant computation of the rank order filtering on a SIMD (single instruction multiple data) mesh processor. The proposed approach improves over a previous approach in two respects: by changing the data dependency in the execution of the rank order filtering, a new algorithm with constant execution time complexity can be designed; and by introducing a dependency for the rank values of faulty processing elements (PEs) as computed by neighboring (fault free) PEs, a lower distortion can be achieved for the image enhancement. An algorithm is presented; this algorithm is based on a two-phase technique in which the rank corresponding to each faulty PE is computed by a selected fault free PE. The effect of the rank computation for a faulty PE is restricted within a window of the image, such that no significant overhead is accounted for in execution complexity. This results in a considerable improvement in speed-up ratio, fault-tolerance as well as a lower distortion in the reconstructed image. The proposed approach is also evaluated using experimental results. As the proposed algorithm is directly compatible with a SIMD mesh execution, a discussion of the communication constructs and switching architecture to support array processing is also presented.

Fabrizio Lombardi

Papers

Compression of VLSI test data by arithmetic coding

Location and identification for single and multiple faults in testable redundant PLAs for yield enhancement

A Near-Sensor ECG Delineation and Arrhythmia Classification System

Testing a Nanocrossbar for Multiple Fault Detection

Fault-tolerant rank order filtering for image enhancement