When comparing conventional computing architectures to the architectures
of biological neural systems, we find several striking differences.
Conventional computers use a low number of high performance computing
elements that are programmed with algorithms to perform tasks in a time
sequenced way; they are very successful in administrative applications,
in scientific simulations, and in certain signal processing
applications. However, the biological systems still significantly
outperform conventional computers in perception tasks, sensory data
processing and motory control. Biological systems use a completely dif-
ferent computing paradigm: a massive network of simple processors that
are (adaptively) interconnected and operate in parallel. Exactly this
massively parallel processing seems the key aspect to their success. On
the other hand the development of VLSI technologies provide us with
technological means to implement very complicated systems on a silicon
die. Especially analog VLSI circuits in standard digital technologies
open the way for the implement at ion of massively parallel analog
signal processing systems for sensory signal processing applications and
for perception tasks. In chapter 1 the motivations behind the emergence
of the analog VLSI of massively parallel systems is discussed in detail
together with the capabilities and !imitations of VLSI technologies and
the required research and developments. Analog parallel signal
processing drives for the development of very com- pact, high speed and
low power circuits. An important technologicallimitation in the
reduction of the size of circuits and the improvement of the speed and
power consumption performance is the device inaccuracies or device
mismatch.
