Today's telecommunication networks have become sources of enormous amounts of widely
heterogeneous data. This information can be retrieved from network traffic traces, network …

Artificial intelligence (AI) is an extensive scientific discipline which enables computer
systems to solve problems by emulating complex biological processes such as learning …

Machine learning (ML) has disrupted a wide range of science and engineering disciplines in
recent years. ML applications in optical communications and networking are also gaining …

With the rapid development of Internet and communication systems, both in the aspect of
services and technologies, communication networks have been suffering increasing …

Failure management plays a role of capital importance in optical networks to avoid service
disruptions and to satisfy customers' service level agreements. Machine learning (ML) …

With the rapid development of optical communication systems, more advanced techniques
conventionally used in long-haul transmissions have gradually entered systems covering …

We propose a transfer learning assisted deep neural network (DNN) method for optical-
signal-to-noise ratio (OSNR) monitoring and realize fast remodel to response to various …

To address the open and diverse situation of future optical networks, it is necessary to find a
methodology to accurately estimate the value of a target quantity in an optical performance …

With the development of 5G technology, high definition video and internet of things, the
capacity demand for optical networks has been increasing dramatically. To fulfill the capacity …

A new class of digital signal processing (DSP)-based fiber-longitudinal optical power profile
monitor has recently been proposed and demonstrated toward optical network tomography …