Abstract: A method for speech enhancement, the method may include receiving or generating sound samples that represent sound signals that were received during a given time period by an array of microphones; frequency transforming the sound samples to provide frequency-transformed samples; clustering the frequency-transformed samples to speakers to provide speaker related clusters, wherein the clustering is based on (i) spatial cues related to the received sound signals and (ii) acoustic cues related to the speakers; determining a relative transfer function for each speaker of the speakers to provide speakers related relative transfer functions; applying a multiple multiple output (MIMO) beamforming operation on the speakers related relative transfer functions to provide beamformed signals; and inverse-frequency transforming the beamformed signals to provide speech signals.

Abstract: A method for speech enhancement, the method may include receiving or generating sound samples that represent sound signals that were received during a given time period by an array of microphones; frequency transforming the sound samples to provide frequency-transformed samples; clustering the frequency-transformed samples to speakers to provide speaker related clusters, wherein the clustering is based on (i) spatial cues related to the received sound signals and (ii) acoustic cues related to the speakers; determining a relative transfer function for each speaker of the speakers to provide speakers related relative transfer functions; applying a multiple multiple output (MIMO) beamforming operation on the speakers related relative transfer functions to provide beamformed signals; and inverse-frequency transforming the beamformed signals to provide speech signals.

Abstract: A method for speech enhancement, the method may include receiving or generating sound samples that represent sound signals that were received during a given time period by an array of microphones; frequency transforming the sound samples to provide frequency-transformed samples; clustering the frequency-transformed samples to speakers to provide speaker related clusters, wherein the clustering is based on (i) spatial cues related to the received sound signals and (ii) acoustic cues related to the speakers; determining a relative transfer function for each speaker of the speakers to provide speakers related relative transfer functions; applying a multiple input multiple output (MIMO) beamforming operation on the speakers related relative transfer functions to provide beamformed signals; and inverse-frequency transforming the beamformed signals to provide speech signals.

Abstract: A method for speech enhancement, the method may include receiving or generating sound samples that represent sound signals that were received during a given time period by an array of microphones; frequency transforming the sound samples to provide frequency-transformed samples; clustering the frequency-transformed samples to speakers to provide speaker related clusters, wherein the clustering is based on (i) spatial cues related to the received sound signals and (ii) acoustic cues related to the speakers; determining a relative transfer function for each speaker of the speakers to provide speakers related relative transfer functions; applying a multiple input multiple output (MIMO) beamforming operation on the speakers related relative transfer functions to provide beamformed signals; and inverse-frequency transforming the beamformed signals to provide speech signals.

Abstract: A trajectory tracking system includes a set of dynamic models, a trajectory database, a trajectory handler, a parameter extractor and a classifier. There is one dynamic model per expected obstacle type and it models an expected trajectory of a point of normal incidence (PNI) of the expected obstacle. The trajectory database stores trajectories for a current set of obstacles being tracked. The trajectory handler at least associates incoming detections to existing trajectories and to update the existing trajectories. The parameter extractor periodically extracts parameters from the trajectories and the classifier classifies obstacles associated with the trajectories at least based on the parameters of the trajectories and on associated the dynamic models for the trajectories.

Abstract: A method for speech enhancement, the method may include receiving or generating sound samples that represent sound signals that were received during a given time period by an array of microphones; frequency transforming the sound samples to provide frequency-transformed samples; clustering the frequency-transformed samples to speakers to provide speaker related clusters, wherein the clustering is based on (i) spatial cues related to the received sound signals and (ii) acoustic cues related to the speakers; determining a relative transfer function for each speaker of the speakers to provide speakers related relative transfer functions; applying a multiple input multiple output (MIMO) beamforming operation on the speakers related relative transfer functions to provide beamformed signals; and inverse-frequency transforming the beamformed signals to provide speech signals.

Abstract: A system for detecting a target, the system comprises a transceiver and a signal processor; wherein the transceiver that is configured to: transmit a first pulse train that comprises multiple radio frequency (RF) pulses of a first non-linear polarity; receive first echoes resulting from the transmission of the first pulse train; generate first detection signals that represent the first echoes; and wherein the signal processor is configured to process the first detection signals to provide an estimated polarization orientation of a target; wherein the processing of the first detection signals comprises estimating a Jones matrix of the target.

Abstract: A system for detecting a target, the system comprises a transceiver and a signal processor; wherein the transceiver that is configured to: transmit a first pulse train that comprises multiple radio frequency (RF) pulses of a first non-linear polarity; receive first echoes resulting from the transmission of the first pulse train; generate first detection signals that represent the first echoes; and wherein the signal processor is configured to process the first detection signals to provide an estimated polarization orientation of a target; wherein the processing of the first detection signals comprises estimating a Jonas matrix of the target.

Abstract: A trajectory tracking system includes a set of dynamic models, a trajectory database, a trajectory handler, a parameter extractor and a classifier. There is one dynamic model per expected obstacle type and it models an expected trajectory of a point of normal incidence (PNI) of the expected obstacle. The trajectory database stores trajectories for a current set of obstacles being tracked. The trajectory handler at least associates incoming detections to existing trajectories and to update the existing trajectories. The parameter extractor periodically extracts parameters from the trajectories and the classifier classifies obstacles associated with the trajectories at least based on the parameters of the trajectories and on associated the dynamic models for the trajectories.

Abstract: A method for obstacle detection, the method may include receiving or generating, by a computerized system, detection information about input radio frequency (RF) signals detected by a RF receiver as a result of a transmission of RF output signals towards a space that comprises potential obstacles; and detecting, by the computerized system, obstacles by associating agent behaviors with clusters of input RF signals.

Abstract: A short range detection system, the system may include a transceiver that is configured to: transmit a step frequency pulse train that comprises multiple radio frequency (RF) pulses that are spaced apart from each other and differ from each other by carrier frequency; wherein spectrums of the multiple spaced apart pulses completely fill a frequency range in which multiple carrier frequencies of the multiple pulses reside; receive echoes resulting from a transmission of the step frequency pulse train; generate detection signals that represent the echoes; and a signal processor that is configured to process the detection signals to detect at least one attribute of a target.

Abstract: A method for obstacle detection, the method may include receiving or generating, by a computerized system, detection information about input radio frequency (RF) signals detected by a RF receiver as a result of a transmission of RF output signals towards a space that comprises potential obstacles; and detecting, by the computerized system, obstacles by associating agent behaviors with clusters of input RF signals.

Abstract: A wire detection apparatus comprises antenna means with a transmitter and a receiver, so devised as to form a pulsed radar system, further including polarization control means for controlling the polarization of waves transmitted and/or received through the antenna means, and processing means for identifying returns from wires according to wires' characteristic polarization echoes. The transmitted waves have a wavelength longer than the diameter of wires to be detected and identified. The transmitted waves preferably have a wavelength more than six times longer than the diameter of wires to be detected and identified. The apparatus is so devised as to detect wires suspended in the air.

Abstract: An active noise control (ANC) system may be implemented to both sides of a fan, such that both directions of the noise emitting are treated to reduce the overall noise. The impact on airflow is minimal, and the technique is very effective in a broad range of low frequencies. Passive sound-absorbing materials may be included for attenuation of high frequencies. The resulting quiet fan produces a low level of noise compared to any other device based on fan, which produces the same capacity of airflow. The quiet fan may be incorporated in any mechanical system which requires airflow induction such as: computers, air conditioners, machines, and more.

Abstract: An Active Noise Control (ANC) for controlling a noise produced by a noise source may include an acoustic sensor (212) to sense a noise pattern and to produce a noise signal corresponding to the sensed noise pattern, an estimator (202) to produce a predicted noise signal by applying an estimation function to the noise signal, and an acoustic transducer (216) to produce a noise destructive pattern based on the predicted noise signal.

Abstract: Some demonstrative embodiments include a muffled rack configured to maintain at least one electronic device, wherein the electronic device has an inlet to receive air for cooling the electronic device and an outlet to discharge the air. The muffled rack may be configured to muffle noise emanating from within the rack through an air inlet and/or an air outlet of the rack. Other embodiments are described and claimed.

Abstract: An Active Noise Control (ANC) for controlling a noise produced by a noise source may include an acoustic sensor (212) to sense a noise pattern and to produce a noise signal corresponding to the sensed noise pattern, an estimator (202) to produce a predicted noise signal by applying an estimation function to the noise signal, and an acoustic transducer (216) to produce a noise destructive pattern based on the predicted noise signal.

Abstract: An Active Muffler in the form of a duct having two open ends for conveying air from a within a cabinet to outside the cabinet. A fan or blower is incorporated in the duct. An Automatic Noise Control (ANC) unit is associated with the duct, and at least one microphone and at least one speaker are incorporated in to the duct for noise-reduction. An outer portion of the duct may be sound-absorbing material. the ANC unit may cause noise to be shifted to a frequency that can be absorbed by the sound-absorbing material.

Abstract: An Active Noise Control (ANC) for controlling a noise produced by a noise source may include an acoustic sensor (212) to sense a noise pattern and to produce a noise signal corresponding to the sensed noise pattern, an estimator (202) to produce a predicted noise signal by applying an estimation function to the noise signal, and an acoustic transducer (216) to produce a noise destructive pattern based on the predicted noise signal.

Abstract: Soundproofing a rack by installing at least one duct on at least one panel of the rack, or as part of the side panels of the rack, or is mounted inside the rack as a drawer in such a way that air can flow outside from the rack causing air to flow from the rack through the duct, and providing an active noise control (ANC) system within the duct. Passive noise control may also be provided in the duct. At least one fan may be provided at an inlet of the duct. Fan speed may be controlled, in response to a climactic condition within the rack. The duct may comprise a back panel which is added on or a replacement for an existing back panel of the rack. A muffled inlet may be provided on another external surface of the rack.