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.

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Principles of Model Checking

A novel approach to the control of an automotive engine in the cut-off region is presented. First, a hybrid model which describes the torque generation mechanism and the power-train dynamics is developed. Then, the cut-off control problem is formulated as a hybrid optimization problem, whose solution is obtained by relaxing it to the continuous domain and mapping its solution back into the hybrid domain. A formal analysis as well as simulation results demonstrate the properties and the quality of the control law.

Hybrid Control for Automotive Engine Management: The Cut-Off Case

http://link.springer.com/content/pdf/10.1007/978-94-009-3649-2_5.pdf

Automatic Layout of Integrated Circuits

Buildings are the result of a complex integration of multi-physics subsystems. Besides the obvious civil engineering infrastructure, thermal, electrical, mechanical, control, communication and computing subsystems must co-exist and be operated so that the overall operation is smooth and efficient. This is particularly important for commercial buildings but is also very relevant for residential buildings especially apartment buildings. Unfortunately, the design and deployment of these subsystems is rarely synchronized: lighting, security, heating, ventilation and air conditioning systems are often designed independently. However, simply putting together a collection of sub-systems, albeit optimized, has led to the inefficient buildings of today. Worldwide, buildings consume 42% of all electrical power - more than any other asset - and it can be proven that much of this can be reduced if a holistic approach to design, deployment, and operation is taken. Government agencies, academic institutions, building contractors and owners have realized the significant impact of buildings on the global environment, the electrical grid, and the mission of their organizations. However, the economic impact for all constituencies is still difficult to assess. Government regulations can play a fundamental role, as it has been the case for the transportation industry where regulations on emission and fuel consumption have been the single most important factor of innovation in automotive design. We are convinced that by leveraging technology and utilizing a system-level approach to buildings, they will provide comfort, safety and functionality while minimizing energy cost, supporting a robust electric grid and mitigating environmental impact. Realizing this vision requires adding intelligence from the beginning of the design phase, to deployment, from commissioning to operation, all the way to the end of the building's life cycle. In this issue, we attempt to provide an as-complete-as-possible overview of the activities in the field of smart connected building design automation that attempts to make the vision a reality. The overarching range of such activities includes developing simulation tools for modeling and the design of buildings, and consequently control algorithms proposed to make buildings smarter and more efficient. Furthermore, we will review real-world and large-scale implementation of such control strategies on physical buildings. We then present a formal co-design methodology to design buildings, taking the view that buildings are prime examples of cyber-physical systems where the virtual and physical worlds meet as more traditional products such as thermostats are able to connect online and perform complicated computational tasks to control building temperature effectively. We complete the presentation describing the growing role of buildings in the operation of the smart grid where buildings are not only consumers of energy, but are themselves also providers of services and energy to the grid. The audiences for this monograph are industry professionals and researchers who work in the area of smart buildings, smart cities, and smart grid, with emphasis on energy efficiency, simulation tools, optimal control, and cyber-physical systems for the emerging power markets.

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Smart Connected Buildings Design Automation: Foundations and Trends

This paper presents behavioral representations for detectors and voltage-controlled oscillators that are independent of circuit architectures. Parameter extraction techniques are described. Finally, parameter extraction for a VCO is demonstrated, and an example PLL constructed using the models is simulated and verified against actual chip measurements.

Behavioral Representations For VCO And Detectors In Phase-lock Systems

The problem of minimizing the cycle time of a given pipelined circuit is considered. Existing approaches are sub-optimal since they do not consider the possibility of simultaneously resynthesizing the combinational logic and moving the latches using retiming. In the work of S. Malik et al. (Proc. of the Hawaii Inter. Conf. on System Sciences, 1990) the idea of simultaneous retiming and resynthesis was introduced. The authors use the concepts presented in that work to optimize a pipelined circuit to meet a given cycle time. Given an instance of the pipelined performance optimization problem, an instance of a combinational speedup problem is constructed. A constructive proof is given that the pipelined problem has a solution if and only if the combinational problem has a solution. This result is significant since it shows that it is enough to consider only the combinational speedup problem and all known techniques for that domain can be directly applied to generate a solution for the pipelined problem. >

Alberto Sangiovanni-Vincentelli

Papers

Hybrid Control for Automotive Engine Management: The Cut-Off Case

Automatic Layout of Integrated Circuits

Smart Connected Buildings Design Automation: Foundations and Trends

Behavioral Representations For VCO And Detectors In Phase-lock Systems

Performance optimization of pipelined circuits