On identifiability and information-regularity in parametrized normal distributions

We describe methods to establish identifiability and information-regularity of parameters in normal distributions. Parameters are considered identifiable when they are determined uniquely by the probability distribution and they are information-regular when their Fisher information matrix is full rank. In normal distributions, information-regularity implies local identifiability, but the converse is not always true. Using the theory of holomorphic mappings, we show when the converse is true, allowing information-regularity to be established without having to explicitly compute the information matrix. Some examples are given.This work was supported by the Air Force Office of Scientific Research under Grant no. F49620-93-1-0096, the National Science Foundation under Grant no. MIP-9122753, and the Office of Naval Research under Grant no. N00014-91-J-1298.     

Magnetoencephalography with diversely oriented and multicomponentsensors

To locate endocranial current sources, a magnetoencephalography (MEG) system usually measures the magnetic field at many points around the skull with an array of radial sensors. Despite the success of using radial components of the field, the authors show that using nonradial components may potentially also be beneficial. They demonstrate some benefits of using diversely oriented and multicomponent sensors to measure the nonradial components. A framework is provided for analyzing the accuracy of a system that estimates the location and direction of a current dipole inside a spherical skull. The framework is then used to determine the effect on accuracy of varying the orientations of sensors in an array and, as a consequence, it is found that the radial orientations commonly used in practice are suboptimal for locating dipoles near the array's center. A diversely oriented array that improves performance is presented. The authors show how a single multicomponent sensor can locate a dipole, and derive a simple algorithm for locating a dipole near the sensor     

Structured unitary space-time autocoding constellations

We previously showed that arbitrarily reliable communication is possible within a single coherence interval in Rayleigh flat fading as the symbol duration of the coherence interval and the number of transmit antennas grow simultaneously. This effect, where the space-time signals act as their own channel codes, is called autocoding. For relatively short (e.g., 16-symbol) coherence intervals, a codebook of independent isotropically random unitary space-time signals theoretically supports transmission rates that are a significant fraction of autocapacity with an extremely low probability of error. The exploitation of space-time autocoding requires the creation and decoding of extraordinarily large constellations-typically L = 2⁸⁰. We make progress on the first part of the problem through a random, but highly structured, constellation that is completely specified by log₂ L independent isotropically distributed unitary matrices. The distinguishing property of this construction is that any two signals in the constellation are pairwise statistically independent and isotropically distributed. Thus, the pairwise probability of error, and hence the union bound on the block probability of error, of the structured constellation is identical to that of a fully random constellation of independent signals. We establish the limitations of an earlier construction through a subsidiary result that is interesting in its own right: the square (or for that matter, any integer power greater than one) of an isotropically random unitary matrix is not isotropically random, with the sole exception of the one-by-one unitary matrix     

Communication over a wireless network with random connections

A network of nodes in which pairs communicate over a shared wireless medium is analyzed. We consider the maximum total aggregate traffic flow possible as given by the number of users multiplied by their data rate. The model in this paper differs substantially from the many existing approaches in that the channel connections in this network are entirely random: rather than being governed by geometry and a decay-versus-distance law, the strengths of the connections between nodes are drawn independently from a common distribution. Such a model is appropriate for environments where the first-order effect that governs the signal strength at a receiving node is a random event (such as the existence of an obstacle), rather than the distance from the transmitter. It is shown that the aggregate traffic flow as a function of the number of nodes n is a strong function of the channel distribution. In particular, for certain distributions the aggregate traffic flow is at least n/(logn)/sup d/ for some d>0, which is significantly larger than the O(/spl radic/n) results obtained for many geometric models. The results provide guidelines for the connectivity that is needed for large aggregate traffic. The relation between the proposed model and existing distance-based models is shown in some cases.     

Primary duodenal adenocarcinoma: a ten-year experience with 79 patients

The comet assay is frequently used to measure DNA damage in individual cells. In order to better understand the mechanisms behind the technique, we have studied the behaviour of DNA under different electrophoresis conditions in mammalian cells exposed to gamma radiation. The comet tails obtained after neutral electrophoresis seem to consist of DNA loops which are attached to structures in the nucleus, since the DNA cannot move in the second direction after two-dimensional electrophoresis. When the DNA is labelled by a short pulse, microautoradiography reveals that all label appear in the head of the comets when neutral electrophoresis is applied. After chase incubation, the label moves out into the tails. This gives further support to the view that the DNA loops are fixed to some structure in the nucleus where also the DNA synthesis takes place. Under alkaline electrophoresis conditions, however, the entire comet tails move in the new electrophoresis direction. Thus, it appears that the alkaline comet tails consist of free DNA fragments. Further, the effects of alkaline concentration and sodium chloride during unwinding and electrophoresis are discussed. Throughout the study, a protocol for drying and fixation of the comets has been used.     

Achieving near-capacity on a multiple-antenna channel

Recent advancements in iterative processing of channel codes and the development of turbo codes have allowed the communications industry to achieve near-capacity on a single-antenna Gaussian or fading channel with low complexity. We show how these iterative techniques can also be used to achieve near-capacity on a multiple-antenna system where the receiver knows the channel. Combining iterative processing with multiple-antenna channels is particularly challenging because the channel capacities can be a factor of ten or more higher than their single-antenna counterparts. Using a "list" version of the sphere decoder, we provide a simple method to iteratively detect and decode any linear space-time mapping combined with any channel code that can be decoded using so-called "soft" inputs and outputs. We exemplify our technique by directly transmitting symbols that are coded with a channel code; we show that iterative processing with even this simple scheme can achieve near-capacity. We consider both simple convolutional and powerful turbo channel codes and show that excellent performance at very high data rates can be attained with either. We compare our simulation results with Shannon capacity limits for ergodic multiple-antenna channel.     

Identifiability in array processing models with vector-sensorapplications

We present a bound on the number of sources identifiable in a class of array processing models with multiple parameters and signals per source. The bound is applied to determine the maximum number of uniquely resolvable plane-wave sources in various acoustic and electromagnetic vector-sensor models. We examine the use of a priori information about the sources, the effects of known and unknown noise characteristics, and the presence of nuisance parameters. Connections between identifiability and existence of the Cramer-Rao bound (CRB) are investigated. We show quantitatively how assumptions about the parameters can fundamentally affect the maximum number of identifiable sources     

Polarimetric modeling and parameter estimation with applications toremote sensing

Develops and analyzes two parametric models in which electromagnetic plane waves carrying polarimetric information are received. The first model considers estimation of the polarimetric response of a surface by measuring the reflections of actively generated waves. The second considers estimation of the polarization of passively generated waves. Both models have applications to remote sensing. The authors propose a natural parametrization of the distribution of the received signal. Using the Cramer-Rao bound, they characterize the best possible accuracy of unbiased estimators of these parameters. Simple estimators are given. Both models are fitted into a common framework and compared