Introduction to the issue on adaptation and learning over complex networks
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We consider a complex network of N diffusively coupled stable limit cycle oscillators. Each individual system has its own set of local parameters Λ, characterizing its frequencies and the shape of limit cycle. The Λ are allowed, thanks to appropriate inter ...
It is common for biological networks to encounter situations where agents need to decide between multiple options, such as deciding between moving towards one food source or another or between moving towards a new hive or another. In previous works, we dev ...
Over the past decade, investigations in different fields have focused on studying and understanding real networks, ranging from biological to social to technological. These networks, called complex networks, exhibit common topological features, such as a h ...
How can we localize the source of diffusion in a complex network? Due to the tremendous size of many real networks---such as the Internet or the human social graph---it is usually infeasible to observe the state of all nodes in a network. We show that it i ...
Over the past decade, investigations in different fields have focused on studying and understanding real networks, ranging from biological to social to technological. These networks, called complex networks, exhibit common topological features, such as a h ...
Since the seminal work of Watts in the late 90s, graph-theoretic analyses have been performed on many complex dynamic networks, including brain structures. Most studies have focused on functional connectivity defined between whole brain regions, using imag ...
Networks are everywhere and we are confronted with many networks in our daily life. Networks such as Internet, World Wide Web, social, biological and economical networks have been subject to extensive studies in the last decade. The volume of publications ...
Collective motion is a remarkable phenomenon in biological systems. There have been several models in the literature to regenerate this type of motion, such as averaging consensus strategies where nodes continuously average the velocity vectors of their ne ...
The topic of this special issue deals with a subject matter that has been receiving immense attention from various research communities, and not only within the signal processing community. Discusses research and development in the area of the adaption and ...
Multiscale representations such as the wavelet transform are useful for many signal processing tasks. Graphs are flexible models to represent complex networks and a spectral graph wavelet transform (SGWT) has recently been developed as a generalization of ...
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