Impulse Processing Algorithm for Random Source Signals of Roadheaders That Is Based on Compound Interferometry

The boom-type roadheader is the main equipment for realizing the mechanization of coal drifting in coal mines, and it is an indispensable production equipment in major coal-producing countries. Substantial vibrations are generated during the operation of a roadheader; these vibrations carry substantial energy and, thus, can be regarded as a potential source and used for seismic advance detection purposes in mine drifts. Compared with a conventional exploration source, a roadheader source produces a complex continuous random signal. The shape of a seismic wavelet is uncertain and its duration is relatively long; thus, it must be processed into a conventional pulse signal before it can be used for subsequent processing and analysis. Therefore, based on the advantages of seismic interferometry in random signal processing, two seismic interference techniques, namely, deconvolution and cross-correlation, are introduced for constructing a compound interference algorithm. On the basis of a theoretically derived formula, a random signal impulse processing experiment is conducted using field-acquired source signals from a roadheader; this approach resolves the problem that cross-correlation alone cannot yield ideal results. Hence, a feasible algorithm for the impulse processing of a random signal, namely, the compound interference algorithm, is proposed. The algorithm deconvolves each seismic trace to obtain the reference trace and other receiver traces after compressing the wavelet. Then, the reference trace and each receiver trace are cross-correlated, and the wavelet time delay information of each correlated wavelet pulse, namely, the wavelet time delay information of the receiver trace relative to the reference trace, is obtained. Accordingly, the direct wave and reflected waves are recognized. To evaluate the performance of the algorithm, an algorithm application experiment is conducted for another group of random source signals that were collected by a roadheader under different coal drift conditions. Again, the algorithm processing results are consistent with the single-shot record characteristics of an explosive source. Consequently, the proposed algorithm can satisfy the requirements for engineering exploration and analysis. A comprehensive analysis further demonstrates that the compound interference algorithm is both feasible and effective and that the processed seismic signals can be used for subsequent processing and interpretation.

A low-delay information sharing algorithm for multiple-radio-per-platform networking

In order to ensure the strong real-time information sharing of Aerial Ad hoc Network, a low-delay information sharing algorithm for multiple-radio-per-platform networking is proposed based on the directional transmission capability of phased-array antenna. The algorithm introduces virtual nodes and virtual links in the process of topology generation first. By extracting topology information and choosing link grouping, it can effectively reduce redundant transmission and transmission latency of information sharing. Then, it is verified through simulation that the algorithm can reduce the latency by up to 49.8% and eliminate transmission redundancy. In addition, a direction selection algorithm is proposed for the variation of antenna beam direction. Simulation results show that the algorithm can further reduce the latency of information sharing and ensure the real time of information sharing, thus further improving the network performance.

Quantifying Information and Uncertainty

We examine ways to measure the amount of information generated by a piece of news and the amount of uncertainty implicit in a given belief. Say a measure of information is valid if it corresponds to the value of news in some decision problem. Say a measure of uncertainty is valid if it corresponds to expected utility loss from not knowing the state in some decision problem. We axiomatically characterize all valid measures of information and uncertainty. We show that if measures of information and uncertainty arise from the same decision problem, then they are coupled in that the expected reduction in uncertainty always equals the expected amount of information generated. We provide explicit formulas for the measure of information that is coupled with any given measure of uncertainty and vice versa. Finally, we show that valid measures of information are the only payment schemes that never provide incentives to delay information revelation. (JEL D81, D83)