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- Chi Tang, Fusheng You, Guang Cheng, Dakuan Gao, Feng Fu, Guosheng Yang +1 other
- IEEE Trans. Biomed. Engineering
- 2008

A study on correlation between structure and resistivity variations was performed for live adult human skull. The resistivities of 388 skull samples, excised from 48 skull flaps of patients undergoing surgery, were measured at body temperature (36.5 degrees C) using the well-known four-electrode method in the frequency range of 1-4 MHz. According to… (More)

We consider the estimation of sparse graphical models that characterize the dependency structure of high-dimensional tensor-valued data. To facilitate the estimation of the precision matrix corresponding to each way of the tensor, we assume the data follow a tensor normal distribution whose covariance has a Kronecker product structure. The penalized maximum… (More)

- Guang Cheng, Jian Gong, Wei Ding
- ICN
- 2005

Spatially coordinated packet sampling can be implemented by using a deterministic function of packet content to determine the selection decision for a given packet. In this way, a given packet may be selected at either all points that it passes, or none. Selection amongst the set of packets should appear as random as possible. In this paper we calculate the… (More)

- Guang Cheng, Jian Gong, Wei Ding
- ICNC
- 2005

Traffic behavior in a large-scale network can be viewed as a complicated non-linear system, so it is very difficult to describe the long-term network traffic behavior in a large-scale network. In this paper, according to the non-linear character of network traffic, the time series of network traffic is decomposed into trend component, period component,… (More)

AMS subject classifications: 62G15 62G08 62F30 a b s t r a c t We consider the (profile) empirical likelihood inferences for the regression parameter (and its any sub-component) in the semiparametric additive isotonic regression model where each additive nonparametric component is assumed to be a monotone function. In theory, we show that the empirical… (More)

The penalized profile sampler for semiparametric inference is an extension of the profile sampler method [9] obtained by profiling a penalized log-likelihood. The idea is to base inference on the posterior distribution obtained by multiplying a profiled penalized log-likelihood by a prior for the parametric component, where the profiling and penalization… (More)

This paper concerns semiparametric regression models with additive nonpara-metric components and high dimensional parametric components under spar-sity assumptions. To achieve simultaneous model selection for both nonpara-metric and parametric parts, we introduce a penalty that combines the adap-tive empirical L 2-norms of the nonparametric component… (More)