Minimum entropy of B-spline PDF systems with mean constraint
For the B-spline approximation of the continuous probability density function (PDF), the relationships between the B-spline weights and entropy both in general and under the mean constraint have been analyzed. It provides the conditions under which the minimum entropy can be achieved subject to the mean constraint. The difference between the entropy of continuous and discrete distributions has also been clarified. A minimum entropy controller with the mean constraint is then developed and several simulations are performed to verify the main results.

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: 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: 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: 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: 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: Best of both latency and throughput
abstract: This paper describes the tradeoff between latency performance and throughput performance in a power-constrained environment. We show that the key to achieving both excellent latency performance as well as excellent throughput performance is to dynamically vary the amount of energy expended to process instructions according to the amount of parallelism available in the software. We survey four techniques for achieving variable energy per instruction: voltage/frequency scaling, asymmetric cores, variable-size cores, and speculation control. We estimate the potential range of energies obtainable by each technique and conclude that a combination of asymmetric cores and voltage/frequency scaling offers the most promising approach to design a chip-level multiprocessor that can achieve both excellent latency performance and excellent throughput performance.

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: EXOCHI: architecture and programming environment for a heterogeneous multi-core multithreaded system
abstract: Future mainstream microprocessors will likely integrate specialized accelerators, such as GPUs, onto a single die to achieve better performance and power efficiency. However, it remains a keen challenge to program such a heterogeneous multicore platform, since these specialized accelerators feature ISAs and functionality that are significantly different from the general purpose CPU cores. In this paper, we present EXOCHI: (1) Exoskeleton Sequencer(EXO), an architecture to represent heterogeneous acceleratorsas ISA-based MIMD architecture resources, and a shared virtual memory heterogeneous multithreaded program execution model that tightly couples specialized accelerator cores with generalpurpose CPU cores, and (2) C for Heterogeneous Integration(CHI), an integrated C/C++ programming environment that supports accelerator-specific inline assembly and domain-specific languages. The CHI compiler extends the OpenMP pragma for heterogeneous multithreading programming, and produces a single fat binary with code sections corresponding to different instruction sets. The runtime can judiciously spread parallel computation across the heterogeneous cores to optimize performance and power.
 We have prototyped the EXO architecture on a physical heterogeneous platform consisting of an Intel® Core™ 2 Duo processor and an 8-core 32-thread Intel® Graphics Media Accelerator X3000. In addition, we have implemented the CHI integrated programming environment with the Intel® C++ Compiler, runtime toolset, and debugger. On the EXO prototype system, we have enhanced a suite of production-quality media kernels for video and image processing to utilize the accelerator through the CHI programming interface, achieving significant speedup (1.41X to10.97X) over execution on the IA32 CPU alone.

title: Register renaming and scheduling for dynamic execution of predicated code
abstract: To achieve higher processor performance requires greater synergy between advanced hardware features and innovative compiler techniques. Recent advancement in compilation techniques for predicated execution has provided significant opportunity in exploiting instruction level parallelism. However, little research has been done on how to efficiently execute predicated code in a dynamic microarchitecture. In this paper, we evaluate hardware optimizations for executing predicated code on a dynamically scheduled microarchitecture. We provide two novel ideas to improve the efficiency of executing predicated code. On a generic Intel Itanium processor pipeline model, we demonstrate that, with some microarchitecture enhancements, a dynamic execution processor can achieve about 16% performance improvement over an equivalent static execution processor.

title: Vertex-Disjoint Triangles in Claw-Free Graphs with Minimum Degree at Least Three
abstract: . Our main result is as follows: For any integer , if G is a claw-free graph of order at least and with minimum degree at least 3, then G contains k vertex-disjoint triangles unless G is of order and G belongs to a known class of graphs. We also construct a claw-free graph with minimum degree 3 on n vertices for each such that it does not contain k vertex-disjoint triangles. We put forward a conjecture on vertex-disjoint triangles in -free graphs.