Abstract: Methods, apparatus and systems for wireless sensing based on deep learning are described.

Abstract: Methods, apparatus and systems for wireless human-nonhuman motion detection are described.

Abstract: Methods, apparatus and systems for wireless gait recognition and rhythmic motion monitoring are described. In one example, a described system comprises: a transmitter, a receiver, and a processor. The transmitter is configured for transmitting a first wireless signal towards an object in a venue through a wireless multipath channel of the venue. The receiver is configured for: receiving a second wireless signal through the wireless multipath channel between the transmitter and the receiver. The second wireless signal differs from the first wireless signal due to the wireless multipath channel which is impacted by a rhythmic motion of the object. The processor is configured for: obtaining a time series of channel information (CI) of the wireless multipath channel based on the second wireless signal, monitoring the rhythmic motion of the object based on the time series of CI (TSCI), and triggering a response action based on a result of the monitoring.

Abstract: A CMOS trans-impedance amplifier (TIA) in accordance with the present disclosure can achieve improved bandwidth and sensitivity by utilizing novel shunt-shunt feedback and inductor peaking. The proposed design simultaneously improves 10-Gbps TIA performance in terms of bandwidth and sensitivity, while the TIA may be fabricated through a standard 0.13 ?m CMOS process. Performance of the TIA in accordance with the present disclosure is much better than that of conventional CMOS TIA in the 10-Gbps CMOS TIA design and applications.