Results 231 to 240 of about 190,933 (296)

Research progress on the depth of anesthesia monitoring based on the electroencephalogram

Ibrain, Volume 11, Issue 1, Page 32-43, Spring 2025.
Electroencephalogram (EEG) can noninvasive, continuous, and real‐time monitor the state of brain electrical activity, and the monitoring of EEG can reflect changes in the depth of anesthesia (DOA). The development of artificial intelligence can enable anesthesiologists to extract, analyze, and quantify DOA from complex EEG data.
Xiaolan He, Tingting Li, Xiao Wang
wiley   +1 more source

Technological Evolution in Fintech: A Decadal Scientometric and Systematic Review of Developments and Criticisms

International Journal of Finance &Economics, EarlyView.
ABSTRACT This study aims to classify pivotal fintech innovations and explore the prospects and pitfalls associated with emerging fintech services extensively discussed in the literature. We conducted a multistage systematic review of research published on fintech over the past decade from a technological perspective. Using the Preferred Reporting Items
Muhammad Imran Qureshi, Nohman Khan
wiley   +1 more source

Domain engineered gallium oxide phototransistors enabling intelligent ultraviolet vision with dynamic gating

InfoMat, EarlyView.
Single‐domain Si‐doped β‐Ga2O3 thin films grown on off‐axis sapphire eliminate domain boundaries, improving transport and photogating. Gate‐pulse modulation suppresses persistent photoconductivity, yielding ultrafast response and high detectivity. Integrated into a 24 × 24 array, the devices enable high frame rate DUV imaging and energy‐efficient ...
Jae Young Kim, Byungsoo Kim, Hee A Kim, Gi Baek Nam, Hyuk Jin Kim, Yoon Jung Lee, Seung Ju Kim, Suin Yi, Yongjo Park, Ho Won Jang   +9 more
wiley   +1 more source

Lead‐free inorganic halide perovskite‐based synaptic memory for next generation neuromorphic computing

InfoMat, EarlyView.
Lead‐free inorganic halide perovskites enable resistive switching synaptic devices capable of mimicking biological learning and multimodal information processing, offering a promising platform for next‐generation neuromorphic computing and artificial intelligence hardware. Abstract Inorganic halide perovskites (IHPs) have emerged as promising materials
Subhasish Chanda, Deepak Kumar, Iman Biswas, Manisha Sharma, Youngmin Lee, Sejoon Lee, Sanjeev Kumar Sharma, Aniruddha Mondal   +7 more
wiley   +1 more source

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Fuzzy Neural Networks

Mathematical Biosciences, 1975
In this paper, the McCulloch-Pitts model of a neuron is extended to a more general model which allows the activity of a neuron to be a “fuzzy” rather than an “all-or-none” process. The generalized model is called a fuzzy neuron. Some basic properties of fuzzy neural networks as well as their applications to the synthesis of fuzzy automata are ...
Lee, Samuel C., Lee, Edward T.
openaire   +1 more source

Fuzzy Neural Networks

2000
Hybrid systems combining fuzzy logic, neural networks, genetic algorithms, expert systems are proving their effectiveness in a wide variety of real-world problems.
PETR MUSÍLEK, MADAN M. GUPTA
openaire   +2 more sources

HYBRID FUZZY POLYNOMIAL NEURAL NETWORKS

International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems, 2002
We propose a hybrid architecture based on a combination of fuzzy systems and polynomial neural networks. The resulting Hybrid Fuzzy Polynomial Neural Networks (HFPNN) dwells on the ideas of fuzzy rule-based computing and polynomial neural networks. The structure of the network comprises of fuzzy polynomial neurons (FPNs) forming the nodes of the first
Oh, Sung-Kwun, Kim, Dong-Won, Pedrycz, Witold   +2 more
openaire   +2 more sources

Fuzzy Sets and Neural Networks

Journal of Cybernetics, 1974
Abstract It is possible that a better model for the behavior of a nerve cell may be provided by what might be called a fuzzy neuron, which is a generalization of the McCulloch-Pitts model. The concept of a fuzzy neuron employs some of the concepts and techniques of the theory of fuzzy sets which was introduced by Zadeh [2, 3] and applied to the theory ...
Lee, Samuel C., Lee, Edward T.
openaire   +2 more sources

Quantum neural networks (QNNs): inherently fuzzy feedforward neural networks

IEEE Transactions on Neural Networks, 1997
This paper introduces quantum neural networks (QNNs), a class of feedforward neural networks (FFNNs) inherently capable of estimating the structure of a feature space in the form of fuzzy sets. The hidden units of these networks develop quantized representations of the sample information provided by the training data set in various graded levels of ...
G, Purushothaman, N B, Karayiannis
openaire   +2 more sources