0% Complete
فارسی
Home
/
سیزدهمین کنفرانس بین المللی فناوری اطلاعات و دانش
A Hybrid Method to Reduce the Voltage Consumption in the Spiking Neural Networks
Authors :
Shaghayegh Mehdizadeh saraj
1
Seyyed Amir Asghari
2
Mohammadreza Binesh Marvasti
3
1- Kharazmi University
2- Kharazmi University
3- Kharazmi University
Keywords :
Neuron threshold،Spiking Neural Networks،Time depend coding،Artifical intelligence
Abstract :
With artificial intelligence's tremendous progress in the past decades, the demand for applying artificial intelligence algorithms and architectures in cloud computing has increased. In this regard, the need for neuromorphic hardware that enables training and processing of data generated by edge devices has increased. Different algorithms have been presented in this direction, but they consume a lot of energy and space due to the large number of calculations. Therefore, researchers tried to minimize energy consumption while maintaining accuracy in deep spiking neural networks as the least consuming generation of neural networks. In order to achieve this goal and reduce the number of references to the required memory and space, they have provided various hardware and software methods. In this article, the best architecture is used by examining the amount of energy consumed and the accuracy of different methods of architecture. Also, a hybrid method is proposed to reduce energy consumption in spiking neural networks. The proposed hybrid architecture was implemented on the MNIST dataset, showing that the power consumption is reduced by almost 1% compared to the state-of-the-art architectures. The accuracy of the proposed hybrid algorithm is 95.3%, which is the highest when compared to the architectures using the time-based coding.
Papers List
List of archived papers
رویکردی در تشخیص خودکار بوهای بد در مدل های معماری سازمانی با استفاده از تحلیل گرافی
زهرا رحیمی تمندگانی - شهره آجودانیان
Optimal control of robotic hand for rehabilitation using fractional order systems and EEG signal processing
Mehran Safari Dehnavi - Vahid Safari Dehnavi - Masoud Shafiee
شبکههای نرمافزار محور در کلان داده: مطالعهی راهکارهای امنیتی و چالشها
احسان سلیمانی دهکردی - محمدرضا ملاخلیلی میبدی
Generalized Self-Attentive Spatiotemporal GCN with OPTICS Clustering for Recommendation Systems
Saba Zolfaghari - Seyed Mohammad Hossein Hasheminejad
A Joint Trajectory and Energy Harvesting Method for an UAV Enabled Disaster Response Network
Hosein Mohammadi Firozjae - Javad Zeraatkar Moghaddam - Mehrdad Ardebilipour
A Model-Driven Approach for Automatic Generation of Android Tourism Applications
Sara Adib - Bahman Zamani
A Real-Time and Robust Approach for Banknote Recognition
Hani Abdi - Mohammad Javad Parseh
کنترل کیفیت غیرمتمرکز مبتنی بر هوش ترکیبی در سیستمهای مشارکتی برخط
مهدیه طالب زاده - هاله امین طوسی - محمد اله بخش
PersianRAG A Retrieval Augmented Generation System for Persian Language
Hossein Hosseini - Mohammad Sobhan Zare - Amir Hossein Mohammadi - Arefeh Kazemi - Zahra Zojaji - Mohammad Ali Nematbakhsh
A Novel Approach to Data mining algorithms and IoT based data mining machine learning
Danial Ramezani - Seyed Hossein Siadat
more
Samin Hamayesh - Version 42.5.2