689,684 research outputs found
full-FORCE: A Target-Based Method for Training Recurrent Networks
Trained recurrent networks are powerful tools for modeling dynamic neural
computations. We present a target-based method for modifying the full
connectivity matrix of a recurrent network to train it to perform tasks
involving temporally complex input/output transformations. The method
introduces a second network during training to provide suitable "target"
dynamics useful for performing the task. Because it exploits the full recurrent
connectivity, the method produces networks that perform tasks with fewer
neurons and greater noise robustness than traditional least-squares (FORCE)
approaches. In addition, we show how introducing additional input signals into
the target-generating network, which act as task hints, greatly extends the
range of tasks that can be learned and provides control over the complexity and
nature of the dynamics of the trained, task-performing network.Comment: 20 pages, 8 figure
A Tight Lower Bound on the Controllability of Networks with Multiple Leaders
In this paper we study the controllability of networked systems with static
network topologies using tools from algebraic graph theory. Each agent in the
network acts in a decentralized fashion by updating its state in accordance
with a nearest-neighbor averaging rule, known as the consensus dynamics. In
order to control the system, external control inputs are injected into the so
called leader nodes, and the influence is propagated throughout the network.
Our main result is a tight topological lower bound on the rank of the
controllability matrix for such systems with arbitrary network topologies and
possibly multiple leaders
Modeling micro-macro pedestrian counterflow in heterogeneous domains
We present a micro-macro strategy able to describe the dynamics of crowds in
heterogeneous media. Herein we focus on the example of pedestrian counterflow.
The main working tools include the use of mass and porosity measures together
with their transport as well as suitable application of a version of
Radon-Nikodym Theorem formulated for finite measures. Finally, we illustrate
numerically our microscopic model and emphasize the effects produced by an
implicitly defined social velocity.
Keywords: Crowd dynamics; mass measures; porosity measure; social network
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