CONDITIONS FOR CHINA-US STRATEGIC COOPERATION

From the "Five-clause Agreement Draft" of 1944 to the Shanghai Communiqueof 1972, the strategic relationship between the United States (US) and theChinese Communist Party (CCP) went through a cycle from partners to foes thenback to partners again. Since the end of World War II, a huge number of booksand articles on CCP-US relations have been published both in the United States andChina. Because of their different political background, Chinese and

Moral Hyperbole： Reflections on Moral Genealogy

My goal in this paper is to respond to the objection that naturalistic accounts of morality miss the thicker meaning with which we normally imbue ethics. I concur. This should lead us to doubt our thicker concepts, however, not doubt moral genealogy. Our thicker conceptions are hyperbolic, at best. The underlying algorithm of morality is the evolutionarily stable strategy： conditional cooperation. The content of such agreements can vary, however, and that is where moral hyperbole resides. Still, we like to distinguish good hyperbole from bad hyperbole, but the only standard for such appraisal is whether the hyperbole is consistent with the social glue of evolutionary dynamics.

Distributed Least Squares Algorithm of Continuous-Time Stochastic Regression Model Based on Sampled Data

In this paper,the authors consider the distributed adaptive identification problem over sensor networks using sampled data,where the dynamics of each sensor is described by a stochastic differential equation.By minimizing a local objective function at sampling time instants,the authors propose an online distributed least squares algorithm based on sampled data.A cooperative non-persistent excitation condition is introduced,under which the convergence results of the proposed algorithm are established by properly choosing the sampling time interval.The upper bound on the accumulative regret of the adaptive predictor can also be provided.Finally,the authors demonstrate the cooperative effect of multiple sensors in the estimation of unknown parameters by computer simulations.

Distributed order estimation for continuous-time stochastic systems

In this paper,we investigate the distributed estimation problem of continuous-time stochastic dynamic systems over sensor networks when both the system order and parameters are unknown.We propose a local information criterion(LIC)based on the L_(0)penalty term.By minimizing LIC at the diffusion time instant and utilizing the continuous-time diffusion least squares algorithm,we obtain a distributed estimation algorithm to simultaneously estimate the unknown order and the parameters of the system.By dealing with the effect of the system noises and the coupling relationship between estimation of system orders and parameters,we establish the almost sure convergence results of the proposed distributed estimation algorithm.Furthermore,we give a simulation example to verify the effectiveness of the distributed algorithm in estimating the system order and parameters.