Despite the rapid progress of neuromorphic computing, inadequate capacity and insufficient
representation power of spiking neural networks (SNNs) severely restrict their application …

GBSVM (Granular-ball Support Vector Machine) is a significant attempt to construct a
classifier using the coarse-to-fine granularity of a granular-ball as input, rather than a single …

This article mainly investigates the model design, field programmable gate array (FPGA)
implementation, and prescribed-time fault-tolerant control of a fractional-order (FO) …

Fuzzy neural network (FNN) is a structured learning technique that has been successfully
adopted in nonlinear system modeling. However, since there exist uncertain external …

In clustering fields, the deep graph models generally utilize the graph neural network to
extract the deep embeddings and aggregate them according to the data structure. The …

Since precisely sensing the underwater environment is a challenging prerequisite for safe
and reliable underwater operation, interest in underwater image processing is growing at a …

Measuring the impact of healthcare service quality of hospitals on customer satisfaction Page 1
Corporate & Business Strategy Review / Volume 5, Issue 1, Special Issue, 2024 336 …

It is technically challenging to achieve stable tracking control for strict-feedback systems in
the presence of mismatched uncertainties in control and feedback paths. The underlying …

Most conventional crowd counting methods utilize a fully-supervised learning framework to
establish a mapping between scene images and crowd density maps. They usually rely on a …

In this paper, a stability control issue for a class of single-input single-output (SISO) time-
varying nonlinear systems with mismatched uncertainties and completely unknown time …