Zobrazeno 1 - 10
of 72
pro vyhledávání: '"Lunglmayr, Michael"'
Autor:
Moser, Bernhard A., Lunglmayr, Michael
In contrast to the traditional principle of periodic sensing neuromorphic engineering pursues a paradigm shift towards bio-inspired event-based sensing, where events are primarily triggered by a change in the perceived stimulus. We show in a rigorous
Externí odkaz:
http://arxiv.org/abs/2410.17441
Autor:
Moser, Bernhard A., Lunglmayr, Michael
The linearly inseparable XOR problem and the related problem of representing binary logical gates is revisited from the point of view of temporal encoding and its solvability by spiking neural networks with minimal configurations of leaky integrate-a
Externí odkaz:
http://arxiv.org/abs/2408.05845
Autor:
Moser, Bernhard A., Lunglmayr, Michael
Leaky-integrate-and-fire (LIF) is studied as a non-linear operator that maps an integrable signal $f$ to a sequence $\eta_f$ of discrete events, the spikes. In the case without any Dirac pulses in the input, it makes no difference whether to set the
Externí odkaz:
http://arxiv.org/abs/2402.07954
Spiking neural networks (SNNs) have gained attention in recent years due to their ability to handle sparse and event-based data better than regular artificial neural networks (ANNs). Since the structure of SNNs is less suited for typically used accel
Externí odkaz:
http://arxiv.org/abs/2311.14447
Autor:
Moser, Bernhard A., Lunglmayr, Michael
In spiking neural networks (SNN), at each node, an incoming sequence of weighted Dirac pulses is converted into an output sequence of weighted Dirac pulses by a leaky-integrate-and-fire (LIF) neuron model based on spike aggregation and thresholding.
Externí odkaz:
http://arxiv.org/abs/2305.08012
Autor:
Moser, Bernhard A., Lunglmayr, Michael
In order to ease the analysis of error propagation in neuromorphic computing and to get a better understanding of spiking neural networks (SNN), we address the problem of mathematical analysis of SNNs as endomorphisms that map spike trains to spike t
Externí odkaz:
http://arxiv.org/abs/2305.05772
Automatic detection of faults in optical fibers is an active area of research that plays a significant role in the design of reliable and stable optical networks. A fiber measurement system that combines automated data acquisition and processing repr
Externí odkaz:
http://arxiv.org/abs/2111.02798
In recent years, machine learning methods became increasingly important for a manifold number of applications. However, they often suffer from high computational requirements impairing their efficient use in real-time systems, even when employing ded
Externí odkaz:
http://arxiv.org/abs/2108.03979
Autor:
Lunglmayr, Michael
The division operation is important for many areas of data processing. Especially considering today's demand for hardware accelerators for machine learning algorithms, there is a high demand for an efficient calculation of the division function, e.g.
Externí odkaz:
http://arxiv.org/abs/2105.05747