Output PDF Shaping of Singular Weights System: Monotonical Performance Design
For a group of stochastic systems whose output probability density function (PDF) is modelled by the B-spline neural networks with singular weights dynamics, the output PDF is controlled towards the desired PDF by an innovative optimization design with monotonically decreasing performance. The controller is developed based on the transformed equivalent non-singular system with sufficient conditions given for the monotonic performance.

title: Novel Parameter Identification by Using a High-Gain Observer With Application to a Gas Turbine Engine
abstract: In this study, a novel identification technique, that is high-gain observer-based identification approach, is proposed for systems with bounded process and measurement noises. For system parameters with abnormal changes, an adaptive change detection and parameter identification algorithm is next presented. The presented technique and algorithm are finally applied to the parameter identification of the gas turbine engine by using the recorded input data from the engine test-bed. The identified parameters and the response curves are desirable. The simulations have proved the effectiveness of the proposed procedure compared with the previous identification approach.

title: Robust minimum entropy tracking control with guaranteed stability for nonlinear stochastic systems under modeling errors
abstract: In this paper, robust minimum entropy tracking control problem is considered for nonlinear stochastic systems. The controlled systems are described by nonlinear non-Gaussian difference equations with the un-modeled uncertainty and modeling error, as well as time delays. Entropy is adopted to characterize the uncertainty of the tracking error. The nonlinear multi-step-ahead predictive cost function is used and the relationship between the probability density functions of the input and the tracking error via the uncertain mapping is established. With these formulations, the cost function can be bounded as a nonlinear functional of the control input and the known bounds of the errors. Explicit design algorithms are presented for the robust suboptimal controller and further for the stabilization controllers. The Renyi's entropy has also been used to simplify the cost function. Simulations are given to demonstrate the effectiveness of the proposed control algorithm.

title: An Intelligent Mill Load Switching Control of the Pulverizing System for an Alumina Sintering Process
abstract: This paper proposes an intelligent switching control strategy for the pulverizing system for an alumina sintering process. The control strategy consists of a coordinating controller, a proportional-integral (PI) controller, a rule-based reasoning controller and a switching mechanism. The practical application to a pulverizing system in an alumina sintering process has shown that when the hot air temperature is low and varies frequently, this control strategy ensures that the mill load and the temperature of the mill outlet are both within their required ranges, and also controls the mill load at the level corresponding to the maximum mill output. Moreover, it has been observed that the proposed control strategy can avoid the fault operating condition and effectively reduce the unit energy consumption.

title: Advances in stochastic distribution control
abstract: Stochastic distribution control systems aims at the controller design so as to realize a shape control of the distributions of certain random variables in the process. Once the probability density functions (PDFs) of these variables are used to describe their distributions, the control task is to obtain control signals so that the output PFDs of the system are made to follow their target PDFs. In this paper, a survey of the recent developments on the research of stochastic distribution control systems will be made.

title: Minimum entropy control of nonlinear ARMA systems over a communication network
abstract: In this paper, the entropy concept has been utilized to characterize the uncertainty of the tracking error for nonlinear ARMA stochastic systems over a communication network, where time delays in the communication channels are of random nature. A recursive optimization solution has been developed. In addition, an alternative algorithm is also proposed based on the probability density function of the tracking error, which is estimated by a neural network. Finally, a simulation example is given to illustrate the efficiency and feasibility of the proposed approach.

title: Multiple Instruction Stream Processor
abstract: Microprocessor design is undergoing a major paradigm shift towards multi-core designs, since performance gains come from exploiting thread-level parallelism in the software. To support this trend, we present a novel processor architecture called the multiple instruction stream processing (MISP) architecture. MISP introduces the sequencer as a new category of architectural resource, and defines a canonical set of instructions to support user-level inter-sequencer signaling and asynchronous control transfer. MISP allows an application program to directly manage user-level threads without OS intervention. By supporting the classic cache-coherent shared-memory programming model, MISP does not require a radical shift in the multithreaded programming paradigm. This paper describes the design and evaluation of the MISP architecture for the IA-32 family of microprocessors. Using a research prototype MISP processor built on an IA-32-based multiprocessor system equipped with special firmware, we demonstrate the feasibility of implementing the MISP architecture. We then examine the utility of MISP by (1) assessing the key architectural tradeoffs of the MISP architecture design and (2) showing how legacy multithreaded applications can be migrated to MISP with relative ease

title: Color-based road detection in urban traffic scenes
abstract: Road detection is a key issue for autonomous driving in urban traffic. In this paper, after a brief overview of existing methods, we present a road-area detection algorithm based on color images. This algorithm is composed of two modules: boundaries are first estimated based on the intensity image and road areas are subsequently detected based on the full color image. In the first module, an edge image of the scene is analyzed to obtain the candidates for the left and right road borders and to delimit the area that will subsequently be used to compute the mean and variance of the Gaussian distribution, assumed to be obeyed by the color components of road surfaces. The second module effectively extracts the road area and reinforces boundaries that most appropriately fit the road-extraction result. The combination of these modules can overcome basic problems due to inaccuracies in edge detection based on the intensity image alone and due to the computational complexity of segmentation algorithms based on color images. Experimental results on real road scenes have substantiated the effectiveness of the proposed method.

title: How to fool an unbounded adversary with a short key
abstract: The symmetric encryption problem which manifests itself when two parties must securely transmit a message m with a short shared secret key is considered in conjunction with a computationally unbounded adversary. As the adversary is unbounded, any encryption scheme must leak information about m; in particular, the mutual information between m and its ciphertext cannot be zero. Despite this, a family of encryption schemes is presented that guarantee that for any message space in {0,1}n with minimum entropy n-lscr and for any Boolean function h:{0,1}n rarr {0,1}, no adversary can predict h(m) from the ciphertext of m with more than 1/nomega(1)  advantage; this is achieved with keys of length lscr+omega(logn). In general, keys of length lscr+s yield a bound of 2-Theta(s) on the advantage. These encryption schemes rely on no unproven assumptions and can be implemented efficiently. Applications of this to cryptosystems based on complexity-theoretic assumptions are discussed and, in addition, a simplified proof of a fundamental "elision lemma" of Goldwasser and Micali is provided

title: Processor Performance Modeling using Symbolic Simulation
abstract: We propose a method of analytically characterizing processor performance as a function of circuit latencies. In our approach, we modify traditional simulation to use variables instead of fixed latencies for the internal functional units. The simulation engine then algebraically computes execution times, and the result is a mathematical equation which characterizes the performance space across numerous processor configurations. We discuss the computational complexity issues of this approach and show that instruction chunking and simple equation redundancy checking can make this approach feasible-we can model a large multi-dimensional design space with thousands to millions of design parameter combinations for about 10times the simulation time of a single conventional simulation run. We demonstrate our approach by exploring two different machines: a traditional MlPS-style in-order pipeline and the Intel Graphics

title: Packing Three Copies of a Tree into a Complete Graph
abstract: A three T of order n is said to be 3-placeable if there are three edge-disjoint copies of T in Kn. In this paper we characterize all the trees T such that T is 3-placeable.