Anomaly Detection in Time Series Data Using Spiking Neural Network
One of the crucial issues in anomaly detection problems is identifying abnormal patterns in time series data that contains noise and in unstructured form. In order to deal with this problem, a good detector is needed with a capability to learn the complex features in the datasets and extract useful...
Saved in:
Main Authors: | Bariah, Yusob, Zuriani, Mustaffa, Junaida, Sulaiman |
---|---|
Format: | Article |
Language: | English |
Published: |
American Scientific Publisher
2018
|
Subjects: | |
Online Access: | http://umpir.ump.edu.my/id/eprint/19952/1/Anomaly%20Detection%20in%20Time%20Series%20Data%20using%20Spiking.pdf http://umpir.ump.edu.my/id/eprint/19952/ https://doi.org/10.1166/asl.2018.12980 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Supervised associative learning in spiking neural network
by: Yusoff, Nooraini, et al.
Published: (2010) -
Performance Evaluation of Attention Mechanism and Spiking Neural Networks on sMRI Data for Suicide Ideation Assessment
by: Corrine, Francis, et al.
Published: (2023) -
Stimulus-stimulus association via reinforcement learning in spiking neural network
by: Yusoff, Nooraini, et al.
Published: (2013) -
A Spectrogram Image-Based Network Anomaly Detection System Using Deep Convolutional Neural Network
by: Adnan Shahid, Khan, et al.
Published: (2021) -
Time Series Forecasting of Energy Commodity using Grey Wolf Optimizer
by: Zuriani, Mustaffa, et al.
Published: (2015)