Multilayer neural networks trained with the back-propagation algorithm constitute the best example of a successful gradient based learning technique. Given an appropriate network architecture, gradient-based learning algorithms can be used to synthesize a complex decision surface that can classify high-dimensional patterns, such as handwritten characters, with minimal preprocessing. This paper reviews various methods applied to handwritten character recognition and compares them on a standard handwritten digit recognition task. Convolutional neural networks, which are specifically designed to deal with the variability of 2D shapes, are shown to outperform all other techniques. Real-life document recognition systems are composed of multiple modules including field extraction, segmentation recognition, and language modeling. A new learning paradigm, called graph transformer networks (GTN), allows such multimodule systems to be trained globally using gradient-based methods so as to minimize an overall performance measure. Two systems for online handwriting recognition are described. Experiments demonstrate the advantage of global training, and the flexibility of graph transformer networks. A graph transformer network for reading a bank cheque is also described. It uses convolutional neural network character recognizers combined with global training techniques to provide record accuracy on business and personal cheques. It is deployed commercially and reads several million cheques per day.

Gradient-based learning applied to document recognition

A new heuristic approach for minimizing possibly nonlinear and non-differentiable continuous space functions is presented. By means of an extensive testbed it is demonstrated that the new method converges faster and with more certainty than many other acclaimed global optimization methods. The new method requires few control variables, is robust, easy to use, and lends itself very well to parallel computation.

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Differential Evolution – A Simple and Efficient Heuristic for Global Optimization over Continuous Spaces

Deposits of clastic carbonate-dominated (calciclastic) sedimentary slope systems in the rock record have been identified mostly as linearly-consistent carbonate apron deposits, even though most ancient clastic carbonate slope deposits fit the submarine fan systems better. Calciclastic submarine fans are consequently rarely described and are poorly understood. Subsequently, very little is known especially in mud-dominated calciclastic submarine fan systems. Presented in this study are a sedimentological core and petrographic characterisation of samples from eleven boreholes from the Lower Carboniferous of Bowland Basin (Northwest England) that reveals a >250 m thick calciturbidite complex deposited in a calciclastic submarine fan setting. Seven facies are recognised from core and thin section characterisation and are grouped into three carbonate turbidite sequences. They include: 1) Calciturbidites, comprising mostly of highto low-density, wavy-laminated bioclast-rich facies; 2) low-density densite mudstones which are characterised by planar laminated and unlaminated muddominated facies; and 3) Calcidebrites which are muddy or hyper-concentrated debrisflow deposits occurring as poorly-sorted, chaotic, mud-supported floatstones. These

Phd by thesis

In this paper we present a new data structure for representing Boolean functions and an associated set of manipulation algorithms. Functions are represented by directed, acyclic graphs in a manner similar to the representations introduced by Lee [1] and Akers [2], but with further restrictions on the ordering of decision variables in the graph. Although a function requires, in the worst case, a graph of size exponential in the number of arguments, many of the functions encountered in typical applications have a more reasonable representation. Our algorithms have time complexity proportional to the sizes of the graphs being operated on, and hence are quite efficient as long as the graphs do not grow too large. We present experimental results from applying these algorithms to problems in logic design verification that demonstrate the practicality of our approach.

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Graph-Based Algorithms for Boolean Function Manipulation

Our growing dependence on increasingly complex computer and software systems necessitates the development of formalisms, techniques, and tools for assessing functional properties of these systems. One such technique that has emerged in the last twenty years is model checking, which systematically (and automatically) checks whether a model of a given system satisfies a desired property such as deadlock freedom, invariants, and request-response properties. This automated technique for verification and debugging has developed into a mature and widely used approach with many applications. Principles of Model Checking offers a comprehensive introduction to model checking that is not only a text suitable for classroom use but also a valuable reference for researchers and practitioners in the field. The book begins with the basic principles for modeling concurrent and communicating systems, introduces different classes of properties (including safety and liveness), presents the notion of fairness, and provides automata-based algorithms for these properties. It introduces the temporal logics LTL and CTL, compares them, and covers algorithms for verifying these logics, discussing real-time systems as well as systems subject to random phenomena. Separate chapters treat such efficiency-improving techniques as abstraction and symbolic manipulation. The book includes an extensive set of examples (most of which run through several chapters) and a complete set of basic results accompanied by detailed proofs. Each chapter concludes with a summary, bibliographic notes, and an extensive list of exercises of both practical and theoretical nature.

/pdf/principles-of-model-checking-249iimickz.pdf

Principles of Model Checking

The complexity of today's embedded electronic systems as well as their demanding performance and reliability requirements are such that their design can no longer be tackled with ad hoc techniques while still meeting tight time to-market constraints. In this paper, we present a system level design approach for electronic circuits, utilizing the platform-based design (PBD) paradigm as the natural framework for mixed-domain design formalization. In PBD, a meet-in-the-middle approach allows systematic exploration of the design space through a series of top-down mapping of system constraints onto component feasibility models in a platform library, which is based on bottom-up characterizations. In this framework, new designs can be assembled from the precharacterized library components, giving the highest priority to design reuse, correct assembly, and efficient design flow from specifications to implementation. We apply concepts from design centering to enforce robustness to modeling errors as well as process, voltage, and temperature variations, which are currently plaguing embedded system design in deep-submicron technologies. The effectiveness of our methodology is finally shown on the design of a pipeline A/D converter and two receiver front-ends for UMTS and UWB communications.

/pdf/a-platform-based-methodology-for-system-level-mixed-signal-4n9eltmm7m.pdf

A platform-based methodology for system-level mixed-signal design

http://link.springer.com/content/pdf/10.1007/978-94-009-3649-2_1.pdf

Synthesis of LSI Circuits

DELIGHT. SPICE: an optimization based system for the design of integrated circuits

Buildings to Grid Integration: A Dynamic Contract Approach

A systematic investigation is presented about the robustness of logic synthesis tools to equivalence-preserving transformations of the input Verilog file. We have developed a framework that: 1) parses Verilog behavioral models into an abstract syntax tree; 2) generates random equivalence-preserving transformations on the syntax tree, and; 3) writes the transformed design back in Verilog format. The original and the transformed Verilog descriptions are then checked for equivalence and synthesized. Results show that average (peak) improvements in area of 2.5% (11%) and length of the critical path of 4% (13%) are achievable. Indeed these figures are comparable to recent advancements in logic synthesis ([17] [8] achieve 4.9% (23%) 5% (24%) improvements area-wise, respectively), signaling a relevant lack of robustness in synthesis tools. This lack of robustness suggests that new synthesis algorithms should be evaluated by measuring the average improvement on several transformed files to assess their real contributions to the quality of the results.

Alberto Sangiovanni-Vincentelli

Papers

A platform-based methodology for system-level mixed-signal design

Synthesis of LSI Circuits

DELIGHT. SPICE: an optimization based system for the design of integrated circuits

Buildings to Grid Integration: A Dynamic Contract Approach

Are logic synthesis tools robust