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Signal Detection in Underwater Sound using Wavelets
利用小波检测水下声音信号
This article considers the use of wavelet methods in relation to a common signal processing problem, that of detecting transient features in sound recordings that contain interference or distortion. In this particular case, the data are various types of underwater sounds, and the objective is to detect intermittent departures (potential “signals”) from the background sound environment in the data (“noise”), where the latter may itself be evolving and changing over time. We…
Amendments and Corrections: The Mahalanobis Distance and Elliptic Distributions
《马氏距离与椭圆分布》的修订与勘误
On page 518 the expressions for u2 and v2 should be U2= S2 _ (n3/N2), v2=t72-(m3/2N2). In view of the complexity of the formula (3d 1), it is worth noting that it gives the same numerical results, in a number of examples, as the subsequent formula of Mielke & Berry (1985). It also agrees numerically in these examples with the exact third central moment calculated using the enumeration algorithm of Saunders referred to in our paper.
The Mahalanobis Distance and Elliptic Distributions
马氏距离与椭圆分布
The Mahalanobis distance is shown to be an appropriate measure of distance between two elliptic distributions having different locations but a common shape. This extends a result long familiar in multivariate analysis to a class of nonnormal distributions. It can also be used to show that the sample version of the Mahalanobis distance is appropriate under both estimative and predictive approaches to estimation for the family of multivariate normal distributions differing…
The Mahalanobis distance and elliptic distributions
马氏距离与椭圆分布
The Mahalanobis distance is shown to be an appropriate measure of distance between two elliptic distributions having different locations but a common shape. This extends a result long familiar in multivariate analysis to a class of nonnormal distributions. It can also be used to show that the sample version of the Mahalanobis distance is appropriate under both estimative and predictive approaches to estimation for the family of multivariate normal distributions differing…