Zobrazeno 1 - 10
of 87
pro vyhledávání: '"Baillieul, John P."'
Autor:
Sun, Zexin, Baillieul, John
There is increasing interest in developing the theoretical foundations of networked control systems that illuminate how brain networks function so as to enable sensory perception, control of movement, memory and all the operations that are needed for
Externí odkaz:
http://arxiv.org/abs/2410.06990
Nonlinear differential equations are encountered as models of fluid flow, spiking neurons, and many other systems of interest in the real world. Common features of these systems are that their behaviors are difficult to describe exactly and invariabl
Externí odkaz:
http://arxiv.org/abs/2405.00627
Autor:
Sun, Zexin, Baillieul, John
Leveraging recent advances in neuroscience and control theory, this paper presents a neuromimetic network model with dynamic symmetric connections governed by Hebbian learning rules. Formal analysis grounded in graph theory and classical control esta
Externí odkaz:
http://arxiv.org/abs/2310.02350
We define the complexity of a continuous-time linear system to be the minimum number of bits required to describe its forward increments to a desired level of fidelity, and compute this quantity using the rate distortion function of a Gaussian source
Externí odkaz:
http://arxiv.org/abs/2306.02435
Autor:
Sun, Zexin, Baillieul, John
Building on our recent research on neural heuristic quantization systems, results on learning quantized motions and resilience to channel dropouts are reported. We propose a general emulation problem consistent with the neuromimetic paradigm. This op
Externí odkaz:
http://arxiv.org/abs/2305.03196
Autor:
Sun, Zexin, Baillieul, John
Based on our recent research on neural heuristic quantization systems, we propose an emulation problem consistent with the neuromimetic paradigm. This optimal quantization problem can be solved with model predictive control (MPC) by deriving the cond
Externí odkaz:
http://arxiv.org/abs/2212.09887
Autor:
Sun, Zexin, Baillieul, John
Building on our recent work on {\em neuromimetic control theory}, new results on resilience and neuro-inspired quantization are reported. The term neuromimetic refers to the models having features that are characteristic of the neurobiology of biolog
Externí odkaz:
http://arxiv.org/abs/2205.05013
Drawing inspiration from biology, we describe the way in which visual sensing with a monocular camera can provide a reliable signal for navigation of mobile robots. The work takes inspiration from a classic paper by Lee and Reddish (Nature, 1981, htt
Externí odkaz:
http://arxiv.org/abs/2111.09669
Autor:
Baillieul, John, Sun, Zexin
Stylized models of the neurodynamics that underpin sensory motor control in animals are proposed and studied. The voluntary motions of animals are typically initiated by high level intentions created in the primary cortex through a combination of per
Externí odkaz:
http://arxiv.org/abs/2104.12926
Autor:
Baillieul, John, Kang, Feiyang
Publikováno v:
In Proceedings of IFAC 2020, Virtual World Congress, Berlin, July 13-17,2020
Borrowing terminology from fluid mechanics, the concepts of {\em Eulerian} and {\em Lagrangian optical flow sensing} are introduced. Eulerian optical flow sensing assumes that each photoreceptor in the camera or eye can instantaneously detect feature
Externí odkaz:
http://arxiv.org/abs/2103.00285