World Heart Corporation

W Kurt Dobson

Ken Poppleton

Gill Brent Bearnson

Gill Bearnson

A system configured to predict characteristics of an artificial heart is described. The system includes a processor and memory in electronic communication with the processor, and an artificial neural network configured to receive an input vector of a predetermined length to train the artificial neural network, produce an output vector based on the input vector, and compare the output vector with a target vector of the predetermined length. When the output vector does not match the target vector within a predetermined error rate, the network is configured to adjust at least one weight, and when the output vector matches the target vector within the predetermined error rate, the network is configured to execute the input vector to produce an estimate at least one characteristic of the artificial heart.

Systems and methods for predicting characteristics of an artificial heart using an artificial neural network

There are disclosed systems and methods of determining a fault location on a wire. In an embodiment, a system includes a PN code having a chip-time. Software code is provided for delaying the PN code a series of delays to form delayed PN samples, a sum of the series of delays being less than one chip-time. Software code is provided for summing the delayed PN samples with the PN code to form a summed sequence. Software code is provided for transmitting the summed PN sequence to the wire. Software code is provided for receiving a signal from the wire related to the summed PN sequence. Software code is provided for mixing the signal received from the wire with a delayed copy of the summed PN sequence so as to form a mixed signal. Software code is provided for integrating the mixed signal to map faults. Other embodiments are also disclosed.

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Draper, UT, United States of America

W Kurt Dobson