10 research outputs found
Phase Diagram of Spiking Neural Networks
In computer simulations of spiking neural networks, often it is assumed that
every two neurons of the network are connected by a probability of 2\%, 20\% of
neurons are inhibitory and 80\% are excitatory. These common values are based
on experiments, observations, and trials and errors, but here, I take a
different perspective, inspired by evolution, I systematically simulate many
networks, each with a different set of parameters, and then I try to figure out
what makes the common values desirable. I stimulate networks with pulses and
then measure their: dynamic range, dominant frequency of population activities,
total duration of activities, maximum rate of population and the occurrence
time of maximum rate. The results are organized in phase diagram. This phase
diagram gives an insight into the space of parameters -- excitatory to
inhibitory ratio, sparseness of connections and synaptic weights. This phase
diagram can be used to decide the parameters of a model. The phase diagrams
show that networks which are configured according to the common values, have a
good dynamic range in response to an impulse and their dynamic range is robust
in respect to synaptic weights, and for some synaptic weights they oscillate in
or frequencies, even in absence of external stimuli.Comment: oscillations are studied in this versio
Finite size scaling approach to dynamic storage allocation problem
It is demonstrated how dynamic storage allocation algorithms can be analyzed
in terms of finite size scaling. The method is illustrated in the three simple
cases of the it first-fit, next-fit and it best-fit algorithms, and the system
works at full capacity. The analysis is done from two different points of view
- running speed and employed memory. In both cases, and for all algorithms, it
is shown that a simple scaling function exists and the relevant exponents are
calculated. The method can be applied on similar problems as well.Comment: 9 pages, 4 figures, will apear in Physica
Three Bead Rotating Chain model shows universality in the stretching of proteins
We introduce a model of proteins in which all of the key atoms in the protein
backbone are accounted for, thus extending the Freely Rotating Chain model. We
use average bond lengths and average angles from the Protein Databank as input
parameters, leaving the number of residues as a single variable. The model is
used to study the stretching of proteins in the entropic regime. The results of
our Monte Carlo simulations are found to agree well with experimental data,
suggesting that the force extension plot is universal and does not depend on
the side chains or primary structure of proteins
Scale-free networks with an exponent less than two
We study scale free simple graphs with an exponent of the degree distribution
less than two. Generically one expects such extremely skewed networks
-- which occur very frequently in systems of virtually or logically connected
units -- to have different properties than those of scale free networks with
: The number of links grows faster than the number of nodes and they
naturally posses the small world property, because the diameter increases by
the logarithm of the size of the network and the clustering coefficient is
finite. We discuss a simple prototype model of such networks, inspired by real
world phenomena, which exhibits these properties and allows for a detailed
analytical investigation
Simulation of Droplet Trains in Microfluidic Networks
In this work we show that in a microfluidic network and in low Reynolds
numbers a system can be irreversible because of hysteresis effects.The network,
which is employed in our simulations, is taken from recent experiments. The
network consists of one loop connected to input and output pipes. A train of
droplets enter the system at a uniform rate, but they may leave it in different
patterns, e.g. periodic or even chaotic. The out put pattern depends on the
time interval among the incoming droplets as well as the network geometry and
for some parameters the system is not reversible