A5101654358- Optimization and Variational Analysis
- Advanced Optimization Algorithms Research
- Iterative Methods for Nonlinear Equations
- Fixed Point Theorems Analysis
- Numerical methods in inverse problems
- Sparse and Compressive Sensing Techniques
- Natural Language Processing Techniques
- Advanced Manufacturing and Logistics Optimization
- Translation Studies and Practices
- Complexity and Algorithms in Graphs
- Nonlinear Differential Equations Analysis
- Evaluation Methods in Various Fields
- Fractional Differential Equations Solutions
- Optimization and Packing Problems
- Advanced Memory and Neural Computing
- Advanced Decision-Making Techniques
- Evaluation and Optimization Models
- Education and Critical Thinking Development
- Language, Discourse, Communication Strategies
- Smart Parking Systems Research
- Educational Reforms and Innovations
- Advanced Algorithms and Applications
- Lexicography and Language Studies
- Educational Technology and Pedagogy
- Matrix Theory and Algorithms
South China Normal University
2024-2025
Soochow University
2024
Weifang University
2015-2024
Nanjing University
2024
Hebei University
2024
Henan University
2024
Tianjin Vocational Institute
2022-2024
Renmin University of China
2022-2023
Shandong University of Science and Technology
2018-2020
First Affiliated Hospital of Xinxiang Medical University
2018
In-sensor computing has emerged as an ultrafast and low-power technique for next-generation machine vision. However, in situ training of in-sensor systems remains challenging due to the demands both high-performance devices efficient programming schemes. Here, we experimentally demonstrate artificial neural network (ANN) based on ferroelectric photosensors (FE-PSs). Our FE-PS exhibits self-powered, fast (<30 μs), multilevel (>4 bits) photoresponses, well long retention (50 days), high...
Abstract In this article, we first introduce the concept of T -mapping a finitefamily strictly pseudononspreading mapping "Equation missing"<!-- image only, no MathML or LaTex -->, and show that fixed point set is common points of"Equation --> quasi-nonexpansive mapping.Based on -mapping, propose simultaneousiterative algorithm to solve split equality problem with way selectingthe stepsizes which does not need any prior information about operatornorms. The sequences generated by weakly...
SrFeOx (SFO) offers a topotactic phase transformation between an insulating brownmillerite SrFeO2.5 (BM-SFO) and conductive perovskite SrFeO3 (PV-SFO) phase, making it competitive candidate for use in resistive memory neuromorphic computing. However, most of existing SFO-based memristors are nonvolatile devices which struggle to achieve short-term synaptic plasticity (STP). To address this issue realize STP, we propose leverage ferroelectric polarization effectively draw ions across the...
In this paper, we study the solutions for nonlinear fractional differential equations with p-Laplacian operator nonlocal boundary value problem in a Banach space. By means of technique properties Kuratowski noncompactness measure and Sadovskii fixed point theorem, establish some new existence criteria problem. As application, an interesting example is provided to illustrate main results.
There are two parts included in traditional imaging diagnosis teaching: theoretical lessons and experimental lessons. Most of the time, lesson is a review lesson. The teacher centre course students passive learners. Thus, this study we patient problem our education. lessen was used to discuss prior knowledge, discussion analysis problems arranged under class, synthesize test newly acquired information. aim determine whether or not integration problem- lecture-based learning teaching modes...
Multi-carrier modulation is attractive for high-speed passive optical network. However, a given system, its capacity limited by the system bandwidth and number of effective data subcarriers. With increase baud rate subcarriers, signal distortion becomes serious. In this work, we propose nonlinear equalizer (NLE), mainly composed 2-order Volterra filter complex-valued neural network channel estimator, to mitigate severe distortion. We experimentally demonstrate evaluate it in spectral...
In this paper, we study the split equality feasibility problem and present two algorithms for solving with special structure.We prove weak convergence of these under mild conditions.Especially, selection stepsize is only dependent on information current iterative points, but independent from prior knowledge operator norms.These provide new ideas problem.Numerical results demonstrate effectiveness algorithms.
In this article, based on M-identity tensor, we establish some parameterized S-type inclusion intervals for fourth-order partially symmetric tensors. The new are tighter than existing results. Furthermore, upper bounds the M-spectral radius of tensors obtained. As applications, as parameter WQZ-algorithm can make algorithm more rapidly converge to largest M-eigenvalue Finally, propose two sufficient conditions M-positive definiteness
We introduce an iterative method to approximate a common solution of split variational inclusion problem and fixed point for nonexpansive semigroups with way selecting the stepsizes which does not need any prior information about operator norms in Hilbert spaces. prove that sequences generated by proposed algorithm converge strongly element set solutions points one-parameter semigroups. Moreover, numerical results demonstrate performance convergence our result, may be viewed as refinement...
We study a kind of split equality fixed point problem which is an extension problem. propose simultaneous iterative algorithm with way selecting the step length does not need any priori information about operator norms and prove that sequences generated by method converge weakly to solution this Some numerical results are shown confirm feasibility efficiency proposed methods.
Many practical applications impose challenges of selecting required elements from a vast amount data with requirement maximizing non-submodular set functions. In this paper, we design two algorithms for the problem normalized monotone function cardinality constraint. By utilizing concept diminishing-return ratio, first propose one pass algorithm called {\scshape Non-SubModular-Sieve-Streaming}$^{++}$ attaining an approximation ratio $...
<title>Abstract</title> In-sensor computing has emerged as an ultrafast and low-power technique for next-generation machine vision. However, in situ training of in-sensor systems remains challenging due to the demands both high-performance devices efficient programming schemes. Here, we experimentally demonstrate artificial neural network (ANN) based on ferroelectric photosensors (FE-PSs). Our FE-PS exhibits self-powered, fast (<30 μs), multilevel (>4 bits) photoresponses, well long...