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Modern data storage systems are extremely large and consist of several tens or hundreds of nodes. In such systems, node failures are daily events, and safeguarding data from them poses a serious design challenge. The focus of this thesis is on the data rel ...
Inference from data is of key importance in many applications of informatics. The current trend in performing such a task of inference from data is to utilise machine learning algorithms. Moreover, in many applications that it is either required or is pref ...
This paper presents a digital, transistor level implemented neo-fuzzy neural network. This type of neural network is particularly well suited for real-time applications like those encountered in signal processing and nonlinear system identification. We con ...
A neuromotor model of handwritten stroke generation, in which stroke velocities are expressed as a Fourier-style decomposition of oscillatory neural activities, is presented. The neural network architecture consists of an input or stroke-selection layer, a ...
Magnetic nanostructures have long been in the focus of intense research in the magnetic storage industry. For data storage the nonvolatility of magnetic states is of utmost relevance. As information technology generates the need for higher and higher data- ...
The organization of connectivity in neuronal networks is fundamental to understanding the activity and function of neural networks and information processing in the brain. Recent studies show that the neocortex is not only organized in columns and layers b ...
A cellular hardware implementation of a spiking neural network with run-time reconfigurable connectivity is presented. It is implemented on a compact custom FPGA board which provides a powerful reconfigurable hardware platform for hardware and software des ...
For further miniaturization of magnetic data storage devices, instruments for exploring magnetic nanostructures are needed. Hall sensors provide a non invasive technique for quantitative magnetic field detection. In contrast to the highly sensitive semicon ...
The patent describes a method for representing a network of spiking neurons in a digital microcontrollers and ways to automatically synthetize an architecture for a specific problem using an evolutionary procedure. Both the neural representation and the ev ...
Challenges in nanotechnology today involve controlling dimensions, inter-particle spacing, surface coverage and behavior/response of functional nanostructures. Creating or placing nanostructures on surfaces is important for applications like data storage, ...
