A new frequency response based model reduction technique is presented for use in the mid-frequency range. The reduction was designed to avoid the use of modal based correlation metrics, which are known to fail in systems with high modal density. A transformation matrix based on a set of complex shapes extracted from the frequency response is used to reduce the impedance matrix to the sensor loc...

In this paper, we consider a privacy preserving scenario where users in the network want to perform distributed target source estimation with a wireless acoustic sensor network (WASN), without revealing the actual source of interest to other entities in the network. This implies that users do not share the steering vector of the beamformer with any other party. For distributed multi-channel noi...

Closed orbit theory is generalized to the semiclassical calculation of cross-correlated recurrence functions for atoms in external fields. The cross-correlation functions are inverted by a high resolution spectral analyzer to obtain the semiclassical eigenenergies and transition matrix elements. The method is demonstrated for dipole transitions of the hydrogen atom in a magnetic field. This is ...

A new sliced orthogonal nonlinear generalized (SONG) decomposition for image processing can be useful for image representation. We examine the use of this representation for two-class pattern recognition in the presence of noise. The SONG correlation is defined and expressed by means of a diagonal matrix representation. Common linear correlation, binary correlation and morphological correlation...

We propose a simple but efficient method for modifying Walsh-Hadamard sequences to achieve correlation properties suited for asynchronous DS CDMA applications. The proposed method can be used to minimize the mean square value of aperiodic cross-correlation or the mean square value of aperiodic autocorrelation, the maximum value of aperiodic cross-correlation functions, merit factor or other pro...

The bulk of the stock market correlation matrix is not pure noise Abstract We analyse the structure of the distribution of eigenvalues of the stock market correlation matrix with increasing length of the time series representing the price changes. We use 100 highly-capitalized stocks from the American market and relate result to the corresponding ensemble of Wishart random matrices. It turns ou...

The bulk of the stock market correlation matrix is not pure noise Abstract We analyse the structure of the distribution of eigenvalues of the stock market correlation matrix with increasing length of the time series representing the price changes. We use 100 highly-capitalized stocks from the American market and relate result to the corresponding ensemble of Wishart random matrices. It turns ou...