Stochastic dynamics of a finite-size spiking neural network

We present a simple Markov model of spiking neural dynamics that can be analytically solved to characterize the stochastic dynamics of a finite-size spiking neural network. We give closed-form estimates for the equilibrium distribution, mean rate, variance and autocorrelation function of the network activity. The model is applicable to any network where the probability of firing of a neuron in the network only depends on the number of neurons that fired in a previous temporal epoch. Networks with statistically homogeneous connectivity and membrane and synaptic time constants that are not excessively long could satisfy these conditions. Our model completely accounts for the size of the network and correlations in the firing activity. It also allows us to examine how the network dynamics can deviate from mean-field theory. We show that the model and solutions are applicable to spiking neural networks in biophysically plausible parameter regimes

Drift-Free Indoor Navigation Using Simultaneous Localization and Mapping of the Ambient Heterogeneous Magnetic Field

In the absence of external reference position information (e.g. GNSS) SLAM has proven to be an effective method for indoor navigation. The positioning drift can be reduced with regular loop-closures and global relaxation as the backend, thus achieving a good balance between exploration and exploitation. Although vision-based systems like laser scanners are typically deployed for SLAM, these sensors are heavy, energy inefficient, and expensive, making them unattractive for wearables or smartphone applications. However, the concept of SLAM can be extended to non-optical systems such as magnetometers. Instead of matching features such as walls and furniture using some variation of the ICP algorithm, the local magnetic field can be matched to provide loop-closure and global trajectory updates in a Gaussian Process (GP) SLAM framework. With a MEMS-based inertial measurement unit providing a continuous trajectory, and the matching of locally distinct magnetic field maps, experimental results in this paper show that a drift-free navigation solution in an indoor environment with millimetre-level accuracy can be achieved. The GP-SLAM approach presented can be formulated as a maximum a posteriori estimation problem and it can naturally perform loop-detection, feature-to-feature distance minimization, global trajectory optimization, and magnetic field map estimation simultaneously. Spatially continuous features (i.e. smooth magnetic field signatures) are used instead of discrete feature correspondences (e.g. point-to-point) as in conventional vision-based SLAM. These position updates from the ambient magnetic field also provide enough information for calibrating the accelerometer and gyroscope bias in-use. The only restriction for this method is the need for magnetic disturbances (which is typically not an issue indoors); however, no assumptions are required for the general motion of the sensor.Comment: ISPRS Workshop Indoor 3D 201

Rural Poverty in China: Problem and Policy

This paper describes the economic conditions of rural China regarding poverty. By dividing the problem of rural poverty into three components it explains why rural poverty is China’s No. 1 economic problem in spite of the significant improvement in the living standard of the rural population. After discussing the solution proposed by the Chinese government it raises two policy questions, one concerning a proposal to eliminate the operational functions of township governments in the streamlining of the local government structure and the second on the possibility of controlling the abuse of power by local party officials that infringes on the rights of the farmers. A comparison with the conditions in India is provided.

Rational Expectations is Not Necessarily Valid for Econometric

Marcoeconomics

China's Economic Policy in the Context of the Asian Finanacial Crisis

This paper is based closely on the author's Y. C. Jao lecture presented to the Hong Kong Economic Association in November 1998.Macroeconomics

Equity Premium and Consumption Sensitivity When the Consumer- Investor Allows for Unfavorable Circumstances

Introducing one additional element due to possible misfortune to the return of each of two assets in the basic model of Samuelson (Rev.Econom.Statist.51 (1969)239)on optimum portfolio and consumption decisions,this paper resolves both the excess equity premium and the excess consumption sensitivity puzzles.This uni ed treatment provides a framework to study how important state variables will a ect the change in aggregate consumption which is consid- ered unpredictable in one formulation of the permanent income hypothesis.The implications of the theory agree with empirical results reported here and elsewhere.The theoretical framework appears to be simple and powerful as compared with alternative theories to explain the two puzzles.Optimum consumption and investment;Asset pricing;Consumption sensitivity;Robust control; The Lagrange method

Shanghai Stock Prices as Determined by the Present Value Model

Derived from the present-value model of stock prices, our model implies that the log stock price is a linear function of expected log dividends and the expected rate of growth of dividends where expectations are formed adaptively. The model explains very well the prices of 47 stocks traded on the Shanghai Stock Exchange observed at the beginning of 1996, 1997, and 1998. The estimated parameters are remarkably similar to those reported for stocks traded on the Hong Kong Stock Exchange and the New York Stock Exchange.Finance