Adversarial dictionary learning for a robust analysis and modelling of spontaneous neuronal activity

Troullinou, Eirini; Tsagkatakis, Grigorios; Palagina, Ganna; Papadopouli, Maria; Smirnakis, Stelios M.; Tsakalides, Panagiotis

doi:10.1016/j.neucom.2020.01.041

Cited by 4 publications

(3 citation statements)

References 31 publications

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“…The processing of sensors and brightness in the indoor lighting control system is also not negligible [9][10]. In the design of the system in this paper, TCRT5000 is used to detect the human body in the current environment; BH1750 detects the brightness in the current environment in real time.…”

Section: B Environmental Testing Unitmentioning

confidence: 99%

Design and Research of Indoor Lighting Control System Based on the STM32

Tian

Zhang

Liu

et al. 2022

International Journal of Advanced Network, Monitoring and Controls

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After the completion of the process of industrialization in the world, a large number of electrified equipment appeared, people's daily life is also more and more dependent on electricity security, electricity consumption has risen sharply. At present, various lights driven by electricity play a crucial role in our daily life, which is also the main cause of electricity consumption. We often notice that even when the room is empty, or during the day, the lights are still on, which is a waste of electricity. The waste of power resources caused by traditional lighting equipment cannot be ignored. Therefore, intelligent home furnishing equipment is the favored object of people. So here for a kind of indoor lighting control system is designed, in order to meet the lighting needs on the basis of more humane, more importantly, can save power resources. With the rapid application of automation in daily life and the continuous development of computer technology, lighting control has become increasingly intelligent and automated. The control function of the system is realized by the STM32F103 chip, the illumination is automatically detected by the BH1750 module, and the time parameters are recorded and fed back by the DS3231 clock module. The infrared reflection sensor is used to detect whether there are people in the room. When there is no one, the light will be automatically turned off to save energy. If there are people, when the ambient light intensity is lower than the set value, the light will be automatically turned on to ensure the comfort of the ambient brightness. And can use OLED module real-time display indoor light intensity, number of people and working time. This indoor lighting control system can not only automatically turn on the light according to the environment, but also detect whether there is a human body in the current environment and turn on or off the light by itself, which has more practical significance.

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Section: B Environmental Testing Unitmentioning

confidence: 99%

Design and Research of Indoor Lighting Control System Based on the STM32

Tian

Zhang

Liu

et al. 2022

International Journal of Advanced Network, Monitoring and Controls

View full text Add to dashboard Cite

show abstract

Section: B Environmental Testing Unitmentioning

confidence: 99%

Design and Research of Indoor Lighting Control System Based on the STM32

Fan,

Zhang,

Kang

et al. 2022

International Journal of Advanced Network, Monitoring and Controls

View full text Add to dashboard Cite

After the completion of the process of industrialization in the world, a large number of electrified equipment appeared, People's Daily life is also more and more dependent on electricity security, electricity consumption has risen sharply. At present, various lights driven by electricity play a crucial role in our daily life, which is also the main cause of electricity consumption. We often notice that even when the room is empty, or during the day, the lights are still on, which is a waste of electricity. The waste of power resources caused by traditional lighting equipment cannot be ignored. Therefore, intelligent home furnishing equipment is the favored object of people. So here for a kind of indoor lighting control system is designed, in order to meet the lighting needs on the basis of more humane, more importantly, can save power resources. With the rapid application of automation in daily life and the continuous development of computer technology, lighting control has become increasingly intelligent and automated. The control function of the system is realized by the STM32F103 chip, the illumination is automatically detected by the BH1750 module, and the time parameters are recorded and fed back by the DS3231 clock module. The infrared reflection sensor is used to detect whether there are people in the room. When there is no one, the light will be automatically turned off to save energy. If there are people, when the ambient light intensity is lower than the set value, the light will be automatically turned on to ensure the comfort of the ambient brightness. And can use OLED module real-time display indoor light intensity, number of people and working time. This indoor lighting control system can not only automatically turn on the light according to the environment, but also detect whether there is a human body in the current environment and turn on or off the light by itself, which has more practical significance.

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“…Numerous neurons in the brain rely on neurotransmitters to transmit information. When its energy accumulation exceeds a certain threshold, the potential fluctuation is registered by the electroencephalogram (EEG), a spontaneous rhythmic neuronal activity [1]. EEG is widely applied in medical disease diagnosis and psychological rehabilitation and is often used to monitor human brain activity's emotional changes and cognitive states [2,3].…”

Section: Introductionmentioning

confidence: 99%

EEG recognition model based on wavelet packet decomposition and ConvNet for art design decisions

et al. 2023

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Aiming at the subjective and unquantifiable problems in art design decisions, using EEG (electroencephalogram) to explain individual behavior is an effective solution. However, the accuracy of the traditional method is lower because of the complexity of EEG. Therefore, we propose the WPD-ConvNet recognition model based on wavelet packet decomposition and convolutional networks to enhance the recognition accuracy of EEG. First, subjects wear brain electrode caps to watch four art designs with different styles and need to make decisions. The EEG is collected during this process. Then, we use the WPD to obtain the features of EEG signals from the decomposed optimal subband nodes. Compared with FFT, WPD divides the frequency band through multiple levels to obtain more EEG time-frequency features related to art design decisions. Finally, we construct an convolutional neural network to identify these features. The experimental results show that our proposed EEG recognition model can achieve an accuracy of 88.7%, which is about 10% higher than others.

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Adversarial dictionary learning for a robust analysis and modelling of spontaneous neuronal activity

Cited by 4 publications

References 31 publications

Design and Research of Indoor Lighting Control System Based on the STM32

Design and Research of Indoor Lighting Control System Based on the STM32

Design and Research of Indoor Lighting Control System Based on the STM32

EEG recognition model based on wavelet packet decomposition and ConvNet for art design decisions

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