Results 71 to 80 of about 1,813,184 (347)

Quasi-Matrix and Quasi-Inverse-Matrix Projective Synchronization for Delayed and Disturbed Fractional Order Neural Network

Complexity, 2019
This paper is concerned with the quasi-matrix and quasi-inverse-matrix projective synchronization between two nonidentical delayed fractional order neural networks subjected to external disturbances.
Jinman He, Fangqi Chen, Qinsheng Bi
doaj   +1 more source

Almost Surely Exponential Convergence Analysis of Time Delayed Uncertain Cellular Neural Networks Driven by Liu Process via Lyapunov–Krasovskii Functional Approach

Entropy, 2023
As with probability theory, uncertainty theory has been developed, in recent years, to portray indeterminacy phenomena in various application scenarios.
Chengqiang Wang, Zhifu Jia, Yulin Zhang, Xiangqing Zhao   +3 more
doaj   +1 more source

Hopf Bifurcation and Chaos in Tabu Learning Neuron Models [PDF]

, 2004
In this paper, we consider the nonlinear dynamical behaviors of some tabu leaning neuron models. We first consider a tabu learning single neuron model. By choosing the memory decay rate as a bifurcation parameter, we prove that Hopf bifurcation occurs in
CHUNGUANG LI, Gopalsamy K., GUANRONG CHEN, Hassard B. D., JUEBANG YU, Kurten K. E., XIAOFENG LIAO   +6 more
core   +2 more sources

Deciphering transcriptional plasticity in pancreatic ductal adenocarcinoma reveals alterations in sensory neuron innervation

Molecular Oncology, EarlyView.
Pancreatic sensory neurons innervating healthy and PDAC tissue were retrogradely labeled and profiled by single‐cell RNA sequencing. Tumor‐associated innervation showed a dominant neurofilament‐positive subtype, altered mitochondrial gene signatures, and reduced non‐peptidergic neurons.
Elena Genova, Michele Montrone, Uday Rangaswamy, Francesco Diversi, Irene Schiavo, Denise Ferrarini, Roberta Di Florio, Irene Longo, Michele Coscia, Nicola Zamboni, Giorgia Demontis, Lisa Veghini, Vincenzo Corbo, Remo Sanges, Paul Heppenstall   +14 more
wiley   +1 more source

Adaptive stochastic synchronization of delayed reaction–diffusion neural networks

Measurement + Control, 2020
In this paper, we deal with the adaptive stochastic synchronization for a class of delayed reaction–diffusion neural networks. By combing Lyapunov–Krasovskii functional, drive-response concept, the adaptive feedback control scheme, and linear matrix ...
Weiyuan Zhang, Junmin Li, Jinghan Sun, Minglai Chen   +3 more
doaj   +1 more source

State estimation for discrete-time neural networks with Markov-mode-dependent lower and upper bounds on the distributed delays [PDF]

, 2012
Copyright @ 2012 Springer VerlagThis paper is concerned with the state estimation problem for a new class of discrete-time neural networks with Markovian jumping parameters and mixed time-delays.
B Du, H Bao, H Huang, H Qiao, H Qiao, HR Karimi, J Liang, L Wang, MS Ali, P Balasubramaniam, P Tino, Q Song, Q Zhou, R Yang, S Arik, S Xu, T Ensari, X Li, Xiaohui Liu, Y He, Y He, Y Liu, Y Liu, Y Liu, Y Ou, Yurong Liu, Z Feng, Z Wang, Z Wang, Z Wang, Z Wang, Z Wang, Z Wang, Z Wang, Z Wang, Z Wang, Z Wu, Zidong Wang   +37 more
core   +1 more source

NKCC1: A key regulator of glioblastoma progression

Molecular Oncology, EarlyView.
Glioblastoma (GBM) progression is driven by disrupted chloride cotransporter homeostasis. NKCC1 is highly expressed in stem‐like, astrocytic, and progenitor cells, correlating with earlier recurrence, while overall survival remains unaffected. NKCC1 serves as a prognostic marker and potential therapeutic target, linking chloride transporter imbalance ...
Anja Thomsen, Diana Freitag, Madlen Haase, Christian Senft, Falko Schwarz, Silke Keiner   +5 more
wiley   +1 more source

Fixed time synchronization of delayed quaternion-valued memristor-based neural networks

Advances in Difference Equations, 2020
This paper investigates the fixed time synchronization issue for a class of quaternion-valued memristor-based neural networks (QVMNN) at the presence of time varying delays.
Dingyuan Chen, Weiwei Zhang, Jinde Cao, Chuangxia Huang   +3 more
doaj   +1 more source

Deep neural networks using a single neuron: folded-in-time architecture using feedback-modulated delay loops

Nature Communications, 2021
Development of deep neural networks benefits from new approaches and perspectives. Stelzer et al. propose to fold a deep neural network of arbitrary size into a single neuron with multiple time-delayed feedback loops which is also of relevance for new ...
Florian Stelzer, André Röhm, Raul Vicente, Ingo Fischer, Serhiy Yanchuk   +4 more
doaj   +1 more source

Extended Dissipativity and Non-Fragile Synchronization for Recurrent Neural Networks With Multiple Time-Varying Delays via Sampled-Data Control

IEEE Access, 2021
This paper deals with the extended dissipativity and non-fragile synchronization of delayed recurrent neural networks (RNNs) with multiple time-varying delays and sampled-data control.
R. Anbuvithya, S. Dheepika Sri, R. Vadivel, Nallappan Gunasekaran, Porpattama Hammachukiattikul   +4 more
doaj   +1 more source