VALLE , Maurizio

Intelligent/smart systems have become common practice in many engineering applications. On the other hand, current low cost standard CMOS technology (and future foreseeable developments) makes available enormous potentialities. The next breakthrough will be the design and development of "smart adaptive systems on silicon" i.e. very power and...

Analog VLSI on-chip learning Neural Networks represent a mature technology for a large number of applications involving industrial as well as consumer appliances. This is particularly the case when low power consumption, small size and/or very high speed are required. This approach exploits the computational features of Neural Networks, the...

Algorithms, applications and hardware implementations of neural networks are not investigated in close connection. Researchers working in the development of dedicated hardware implementations de- velop simplied versions of otherwise complex neural algorithms or de- velop dedicated algorithms: usually these algorithms have not been thor- oughly...

In the last few years the amount of electronics inside cars has increased significantly. Current vehicles have implemented highly distributed electronic systems. The high number of Electronic Control Units (ECUs) and the high amount of data which must be exchanged require high bandwidth and reliable communication systems. Flexray is the...

This paper deals with analog VLSI architectures addressed to the implementation of smart adaptive systems on silicon. In particular, we addressed the implementation of artificial neural networks with on-chip learning algorithms with the goal of efficiency in terms of scalability, modularity, computational density, real time operation and power...

Internal vehicle communication networks are becoming highly distributed systems. The increase of the internal vehicle electronic system complexity requires higher performance and reliability, and the necessity of ensuring enough bus signal integrity increases the design verification effort. In this paper we present a system verification...

The CMOS circuit implementation of the feed forward neural primitives of a generic Multi Layer Perceptron network is presented. Basically our approach is based on current mode computation and is aimed at a low power/low voltage circuit implementation; moreover, it is easily scalable to implement network of any size. Experimental results are reported.

In-vehicle communication networks are a complex and safety-critical system, in which system reliability is essential. Network tests and verification by means of behavioral simulations have been widely adopted by the O&Ms. Among a series of advantages, behavioral simulations allow the statistical analysis performace evaluation, which is...