Neural networks have enabled applications in artificial intelligence through machine
learning, and neuromorphic computing. Software implementations of neural networks on …

Terahertz (THz) science and technology have greatly progressed over the past two decades
to a point where the THz region of the electromagnetic spectrum is now a mature research …

Synthetic aperture radar (SAR) image formation can be treated as a class of ill-posed linear
inverse problems, and the resolution is limited by the data bandwidth for traditional imaging …

Compressive Sensing (CS) is a new sensing modality, which compresses the signal being
acquired at the time of sensing. Signals can have sparse or compressible representation …

This tutorial text gives a unifying perspective on machine learning by covering both
probabilistic and deterministic approaches-which are based on optimization techniques …

Wireless sensor networks (WSNs) monitor dynamic environments that change rapidly over
time. This dynamic behavior is either caused by external factors or initiated by the system …

The problem of phase retrieval, ie, the recovery of a function given the magnitude of its
Fourier transform, arises in various fields of science and engineering, including electron …

This paper proposes a spatially common sparsity based adaptive channel estimation and
feedback scheme for frequency division duplex based massive multi-input multi-output …

To fully utilize the spatial multiplexing gains or array gains of massive MIMO, the channel
state information must be obtained at the transmitter side (CSIT). However, conventional …

With the advancement of network and computer technologies, virtual cyberspace keeps
evolving, and Metaverse is the main representative. As an irreplaceable technology that …