Results 21 to 30 of about 12,316 (267)

Input and Output Quantized Feedback Linear Systems

open access: yesIEEE Transactions on Automatic Control, 2010
Although there has been a lot of research on analysis and synthesis of quantized feedback control systems, most results are developed for the case of a single quantizer (either measurement quantization or control signal quantization). In this technical note, we investigate the case of feedback control systems subject to both input and output ...
Daniel Ferreira Coutinho   +2 more
openaire   +2 more sources

Quantization of Continuous Input Variables for Binary Classification [PDF]

open access: yes, 2000
Quantization of continuous variables is important in data analysis, especially for some model classes such as Bayesian networks and decision trees, which use discrete variables. Often, the discretization is based on the distribution of the input variables only whereas additional information, for example in form of class membership is frequently present
Michal Skubacz, Jaakko Hollmén
openaire   +1 more source

A Relaxed Quantization Training Method for Hardware Limitations of Resistive Random Access Memory (ReRAM)-Based Computing-in-Memory

open access: yesIEEE Journal on Exploratory Solid-State Computational Devices and Circuits, 2020
Nonvolatile computing-in-memory (nvCIM) exhibits high potential for neuromorphic computing involving massive parallel computations and for achieving high energy efficiency.
Wei-Chen Wei   +9 more
doaj   +1 more source

Adaptive Output Feedback Control for Constrained Switched Systems with Input Quantization

open access: yesMathematics, 2023
This paper investigates adaptive output feedback control problem for switched uncertain nonlinear systems with input quantization, unmeasured system states and state constraints.
Shuyan Qi, Jun Zhao, Li Tang
doaj   +1 more source

Robust Quantized Consensus of Discrete Multi-Agent Systems in the Input-to-State Sense

open access: yesIEEE Access, 2019
In this paper, we consider the quantized consensus problem of multiple discrete-time integrator agents which suffer from additive noise. Due to the limited communication resources, each agent can only exchange quantized information of finite length with ...
Jiayu Chen, Qiang Ling
doaj   +1 more source

Adaptive Sliding Mode Control for Unmanned Surface Vehicles with Predefined-Time Tracking Performances

open access: yesJournal of Marine Science and Engineering, 2023
This paper is concerned with the trajectory tracking control of unmanned surface vehicles (USVs) subject to input quantization, actuator faults and dead zones.
Tao Jiang, Yan Yan, Shuang-He Yu
doaj   +1 more source

Unmanned ship heading tracking control strategy with state quantization and input quantization

open access: yesZhongguo Jianchuan Yanjiu
ObjectiveThis paper develops a heading tracking design strategy for unmanned ships with state quantization and input quantization in order to address the problem of limited communication at sea for unmanned ships on the water surface.Methods First, a ...
Wei LI, Yu WANG, Jun NING, Zhihui LI
doaj   +1 more source

Quantized Adaptive Decentralized Control for a Class of Interconnected Nonlinear Systems With Hysteretic Actuators Faults

open access: yesIEEE Access, 2018
In this paper, a quantized adaptive decentralized output feedback control is proposed for a class of interconnected nonlinear systems with quantized input and possible number of hysteretic actuators failure up to infinity.
Wakeel Khan   +4 more
doaj   +1 more source

Adaptive Distributed Heterogeneous Formation Control for UAV-USVs with Input Quantization

open access: yesJournal of Marine Science and Engineering
This paper investigates the cooperative formation trajectory tracking problem for heterogeneous unmanned aerial vehicle (UAV) and multiple unmanned surface vessel (USV) systems with input quantization performance.
Jun Ning   +4 more
doaj   +1 more source

Sequential Characteristics Based Operators Disassembly Quantization Method for LSTM Layers

open access: yesApplied Sciences, 2022
Embedded computing platforms such as neural network accelerators deploying neural network models need to quantize the values into low-bit integers through quantization operations.
Yuejiao Wang, Zhong Ma, Zunming Yang
doaj   +1 more source

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