The continuing development of the silicon technology leads to systems with hundreds of processors interconnected by a network on chip (NoC-based MPSoCs). On one hand, the nanotechnology enables to develop such complex systems, but, on the other hand, the vulnerability to faults increases. The literature presents partial fault-tolerant approaches, targeting specific parts of the system, as high-level […]

This paper presents adaptive control structure applied for electrical drive with elastic coupling between motor and load machine. The main speed controller is based on neuro-fuzzy model. Proposed control structure works using all state variables of the two-mass system. Feedbacks coefficients have been calculated analytically. Information about state variables is given by the Luenberger observer. […]

5G mobile networks will very likely include features that allow for a dynamic spectrum access (DSA) in order to exploit spectrum holes of a primary system. The efficient utilization of spectrum holes with minimum impairment of the primary system requires a waveform with a very low adjacent channel leakage ratio as well as robustness to time and […]

Connection strength estimation is widely used in detecting the topology of neuronal networks and assessing their synaptic plasticity. A recently proposed model-based method using the leaky integrate-and-fire model neuron estimates membrane potential from spike trains by calculating the maximum a posteriori (MAP) path. We further enhance the MAP path method using variational Bayes and dynamic causal modeling. […]

This paper introduces a spiking hierarchical model for object recognition which utilizes the precise timing information inherently present in the output of biologically inspired asynchronous Address Event Representation (AER) vision sensors. The asynchronous nature of these systems frees computation and communication from the rigid predetermined timing enforced by system clocks in conventional systems. Freedom from […]