Real-Time Classification of Multivariate Olfaction Data Using Spiking Neural Networks
نویسندگان
چکیده
منابع مشابه
Temporal Pattern Classification using Spiking Neural Networks
A novel supervised learning-rule is derived for Spiking Neural Networks (SNNs) using the gradient descent method, which can be applied on networks with a multi-layered architecture. All existing learning-rules for SNNs limit the spiking neurons to fire only once. Our algorithm however is specially designed to cope with neurons that fire multiple spikes, taking full advantage of the capabilities...
متن کاملReal-Time Musical Beat Induction with Spiking Neural Networks
Beat induction is best described by analogy to the activities of hand clapping or foot tapping, and involves finding important metrical components in an auditory signal, usually music. Though beat induction is intuitively easy to understand it is difficult to define and still more difficult to perform automatically. We will present a model of beat induction that uses a spiking neural network as...
متن کاملrodbar dam slope stability analysis using neural networks
در این تحقیق شبکه عصبی مصنوعی برای پیش بینی مقادیر ضریب اطمینان و فاکتور ایمنی بحرانی سدهای خاکی ناهمگن ضمن در نظر گرفتن تاثیر نیروی اینرسی زلزله ارائه شده است. ورودی های مدل شامل ارتفاع سد و زاویه شیب بالا دست، ضریب زلزله، ارتفاع آب، پارامترهای مقاومتی هسته و پوسته و خروجی های آن شامل ضریب اطمینان می شود. مهمترین پارامتر مورد نظر در تحلیل پایداری شیب، بدست آوردن فاکتور ایمنی است. در این تحقیق ...
Classification capacity of spiking neural networks
We investigate a minimalistic abstraction for a multi-layer spiking neural network (SNN), in order to gain fundamental insight into classifying spatiotemporal patterns using temporal coding. The firing model is based on coincidence detection with temporal binning: a neuron X fires at time t if at least η > 1 upstream neurons fire prior to t such that the spikes arrive at X in an interval [t−δ/2...
متن کاملMoving Target Detection and Classification Using Spiking Neural Networks
We proposed a spiking neural network (SNN) to detect moving target in video streams and classify them into real categorization in this paper. The proposed SNN uses spike trains to encoding information such as the gray value of pixels or feature parameters of the target, detects moving target by simulating the visual cortex for motion detection in biological system with axonal delays and classif...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Sensors
سال: 2019
ISSN: 1424-8220
DOI: 10.3390/s19081841