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

In networked control systems the controller of a physically-distributed plant is implemented as a collection of tightly-interacting, concurrent processes running on a distributed execution platform. The execution platform consists of a set of heterogeneous components (sensors, actuators, and controllers) that interact through a hierarchical communication network. We propose a methodology and a framework for design exploration and automatic synthesis of the communication network. We present how our approach can be applied to the design of control systems for intelligent buildings. The input specification of the control system includes (i) the constraints on the location of its components, which are imposed by the plant, (ii) the communication requirements among the components, and (iii) an estimation of the real-time constraints for the correct behavior of the algorithms implementing the control law. The output produces an implementation of the control networks that is obtained by combining elements from a pre-defined library of communication links, protocols, interfaces, and switches. The implementation is optimal in the sense that it satisfies the given specification while minimizing an objective function that captures the overall cost of the network implementation.

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A communication synthesis infrastructure for heterogeneous networked control systems and its application to building automation and control

We develop an assume-guarantee contract framework for the design of cyber-physical systems, modeled as closed-loop control systems, under probabilistic requirements. We use a variant of signal temporal logic, namely, Stochastic Signal Temporal Logic (StSTL) to specify system behaviors as well as contract assumptions and guarantees, thus enabling automatic reasoning about requirements of stochastic systems. Given a stochastic linear system representation and a set of requirements captured by bounded StSTL contracts, we propose algorithms that can check contract compatibility, consistency, and refinement, and generate a controller to guarantee that a contract is satisfied, following a stochastic model predictive control approach. Our algorithms leverage encodings of the verification and control synthesis tasks into mixed integer optimization problems, and conservative approximations of probabilistic constraints that produce both sound and tractable problem formulations. We illustrate the effectiveness of our approach on a few examples, including the design of embedded controllers for aircraft power distribution networks.

Stochastic Assume-Guarantee Contracts for Cyber-Physical System Design Under Probabilistic Requirements

It is shown that hazards can be optimally eliminated from circuits synthesized starting with a signal transition graph (STG) specification. The proposed approach is based on a linear programming (or integer linear programming) formulation, and as such it can be solved efficiently and optimally for a variety of cost functions. Suggested cost functions optimize either the total padded delay, an estimate of the increase in area, or the maximum cycle time of the complete system. It is also shown that delay padding on all fanouts of STG signals is a necessary and sufficient condition for hazard elimination if the structure and delay of each combinational logic block cannot be changed. Experimental results indicate that the improvements obtained are well worth the added complexity of linear program solution. >

Linear programming for optimum hazard elimination in asynchronous circuits

The idle speed control problem for automotive GDI engines is formalized as a constrained optimal control problem for a hybrid model of the GDI engine, where fuel consumption is the cost function to be minimized. A sub-optimal but effective and easily implementable solution is obtained by resorting to the command governor methodology for a discrete-time abstraction of the hybrid model. Simulation results of the hybrid closed-loop system are presented.

Hybrid command governors for idle speed control in gasoline direct injection engines

Computer aids have been used for both the design and verification of electronic systems for many years. The recent explosion in the complexity of electronic systems that the advent of Very Large Scale Integration (VLSI) has allowed, has made the use of sophisticated computer-aided design tools indispensable. Computer aids will soon also provide key proprietary advantages as semiconductor and system design houses vie for the promising Application-Specific IC (ASIC) market of the next decade. This paper focusses on the techniques critical to both custom and ASIC design, the directions of present research and development for these areas, and future trends. In particular, recent developments in tools for the automated design of combinational logic are reviewed. These techniques include both algorithmic and rule-based approaches.

Alberto Sangiovanni-Vincentelli

Papers

A communication synthesis infrastructure for heterogeneous networked control systems and its application to building automation and control

Stochastic Assume-Guarantee Contracts for Cyber-Physical System Design Under Probabilistic Requirements

Linear programming for optimum hazard elimination in asynchronous circuits

Hybrid command governors for idle speed control in gasoline direct injection engines

CAD tools for ASIC design