Digisonix, Inc.

Nelson Industries, Inc.

Nicolet Instrument Corporation

Nicolet Biomedical, Inc.

Barry D Van Veen

Kurt E Hecox

Michael P Nowak

Daniel J Sebald

Olivier E Leblond

Jon Joseph

An adaptive acoustic attenuation system has distributed nodal processing and a shared state nodal architecture. The system includes a plurality of adaptive filter nodes, each preferably having a dedicated digital signal processor. Each adaptive filter node preferably receives a reference signal and generates a correction signal that drives an acoustic actuator. Each adaptive filter node also shares nodal state vectors with adjacent adaptive filter nodes. The calculation of the nodal correction signals depends both on the reference signal and nodal state vectors received from adjacent adaptive filter nodes. The calculation of nodal state vectors shared with adjacent adaptive filter nodes depends on nodal state vectors received from other adjacent adaptive filter nodes as well as nodal reference signals inputting the adaptive filter node. Adaptation of adaptive weight vectors for generating the correction signals and adaptive weight matrices for generating nodal state signal vectors are adapted in accordance with globally transmitted error signals being back-propagated through the appropriate acoustic and electrical paths. The adaptive filter nodes can be arranged in a linear network topology, or in some other network topology such as but not limited to a random web network topology. The system allows the addition or elimination of additional reference signals and/or acoustic actuators with associated digital signal processing nodes to the system without requiring the system to be reconfigured and without requiring rewriting of software. The system is well-suited for high dimensional MIMO active acoustic attenuation systems.

Adaptive acoustic attenuation system having distributed processing and

Using a set of basis vectors, output from an adaptive control filter or adaptation of the control filter can be selectively constrained. Selected basis vectors define an adaptation subspace. The adaptive control filter can have a bank of non-adaptive FIR filters and a linear combiner with adaptive weights and fixed weights, or can use projection methods in conjunction with conventional adaptive FIR or IIR filter models. Filtered-X and filtered-U techniques can also be used.

Adaptive control system with selectively constrained ouput and adaptation

The effect of noise in the displayed information obtained from transcranial Doppler measurements is reduced by estimating the spectra of the returned Doppler signal as the average of Fourier spectra computed using multiple windows for the data being analyzed. The windows are chosen so that the spectra from different windows are approximately statistically independent, thereby reducing the variance of the spectrum by the averaging process. The Doppler data may be obtained by applying repeated pulses of ultrasonic energy to the head of a subject and isolating the Doppler frequency components of the return signal to obtain a set of data from a selected number of pulses. The data set so obtained has the multiple window functions applied thereto to obtain multiple windowed data sets which are operated on, as in a digital signal processor, to obtain multiple discrete Fourier transforms of the windowed data sets. A power spectrum is estimated as the averaged sum of the squares of the magnitudes of each of the discrete Fourier transforms. The spectra obtained from data sets gathered in sequence may be displayed to an operator to show the spectral content of the return signal over time, which corresponds to the velocity of blood flow at a position within the head of the subject as a function of time.

Method and apparatus for transcranial doppler sonography

Signals from plural electrodes placed at known positions on the head of an individual are digitized and processed in a computer processor which includes a bank of spatial filters. The filters are designed to meet a linearly constrained minimum variance criterion so that they each substantially pass signal energy from a location within the brain known with respect to the electrodes while rejecting signal energy from other locations within the brain. The outputs of the filters can be used to estimate the signal power at each of the locations in the brain, or the dipole moment at each location, and this information can be displayed on a display device to provide a map of source activity within the brain. The spatial filters do not require prior knowledge of the number of sources, and the number of discrete sources can be identified as well as the location, power, and dipole moment of the sources. This information can be used when a stimulus is applied to the individual to determine the regions of the brain which respond to the stimulus, or to localize neural activity in the brain to identify the location of pathology within the brain.

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McFarland, WI, United States of America

Barry D Van Veen