Abstract: A method, non-transitory computer readable medium, and system for multiple-input multiple-output for blind identification that includes receiving an input signal, originated as an output signal of a transmitter, at a receiver. A signal processing module can obtain the input signal from the receiver. The signal processing module can use a finite impulse response filter and one or more matrices derived from the input signal to minimize a cost function and obtain a parameter matrix. The parameter matrix can then be used to estimate the output signal by generating one or more Toeplitz matrices using the parameter matrix.

Abstract: A system, method, and non-transitory computer readable medium that perform blind signal estimation for single-input multiple-output systems. The method can include receiving, by the two or more receiver antennas of the receiver, an observed signal comprising the input signal and an additive noise term. The method can then form a data matrix using the observed signals from the two or more receiver antennas. The method can also include computing a singular value decomposition of the data matrix. The singular value decomposition can then be used to generate a parameter matrix. The method can then form a Toeplitz signal matrix using the parameter matrix. The method can estimating the input signal using the Toeplitz signal matrix.

Abstract: A device, method, and non-transitory computer readable medium that for two-dimensional blind single-input multiple-output channel identification for image restoration. The method includes receiving, by a receiver having independent channels, a two-dimensional image data matrix then transforming the received two-dimensional image data matrix to a one-dimensional image vector. Channel parameters can then be estimated using the one-dimensional image vector. The method can then construct a restored image using the estimated channel parameters and the two-dimensional image data matrix.

Abstract: An apparatus, method, and non-transitory computer readable medium that can mitigate wireless channel impairments in seismic data transmission using deep neural networks is disclosed. The apparatus includes a receiving circuitry to receive seismic data and a processing circuitry. The processing circuitry is configured to apply a blind system identification process to the seismic data to estimate a channel impulse response of the seismic data, apply an optimum equalization process to obtain estimated seismic data based on the channel impulse response, process the estimated seismic data to generate processed seismic data, classify the processed seismic data into a first group of seismic data each of which has a signal-to-noise ratio (SNR) less than an SNR threshold and a second group of seismic data each of which has an SNR no less than the SNR threshold, and enhance the SNR of each of the first group of seismic signals.