2,082 research outputs found
Synchronizing noisy nonidentical oscillators by transient uncoupling
Synchronization is the process of achieving identical dynamics among coupled
identical units. If the units are different from each other, their dynamics
cannot become identical; yet, after transients, there may emerge a functional
relationship between them -- a phenomenon termed "generalized synchronization."
Here, we show that the concept of transient uncoupling, recently introduced for
synchronizing identical units, also supports generalized synchronization among
nonidentical chaotic units. Generalized synchronization can be achieved by
transient uncoupling even when it is impossible by regular coupling. We
furthermore demonstrate that transient uncoupling stabilizes synchronization in
the presence of common noise. Transient uncoupling works best if the units stay
uncoupled whenever the driven orbit visits regions that are locally diverging
in its phase space. Thus, to select a favorable uncoupling region, we propose
an intuitive method that measures the local divergence at the phase points of
the driven unit's trajectory by linearizing the flow and subsequently
suppresses the divergence by uncoupling
Cyclic Prefix-Free MC-CDMA Arrayed MIMO Communication Systems
The objective of this thesis is to investigate MC-CDMA MIMO systems where
the antenna array geometry is taken into consideration. In most MC-CDMA
systems, cyclic pre xes, which reduce the spectral e¢ ciency, are used. In order
to improve the spectral efficiency, this research study is focused on cyclic pre x-
free MC-CDMA MIMO architectures.
Initially, space-time wireless channel models are developed by considering the
spatio-temporal mechanisms of the radio channel, such as multipath propaga-
tion. The spatio-temporal channel models are based on the concept of the array
manifold vector, which enables the parametric modelling of the channel.
The array manifold vector is extended to the multi-carrier space-time array
(MC-STAR) manifold matrix which enables the use of spatio-temporal signal
processing techniques. Based on the modelling, a new cyclic pre x-free MC-
CDMA arrayed MIMO communication system is proposed and its performance
is compared with a representative existing system. Furthermore, a MUSIC-type
algorithm is then developed for the estimation of the channel parameters of the
received signal.
This proposed cyclic pre x-free MC-CDMA arrayed MIMO system is then
extended to consider the effects of spatial diffusion in the wireless channel. Spatial
diffusion is an important channel impairment which is often ignored and the
failure to consider such effects leads to less than satisfactory performance. A
subspace-based approach is proposed for the estimation of the channel parameters
and spatial spread and reception of the desired signal.
Finally, the problem of joint optimization of the transmit and receive beam-
forming weights in the downlink of a cyclic pre x-free MC-CDMA arrayed MIMO
communication system is investigated. A subcarrier-cooperative approach is used
for the transmit beamforming so that there is greater flexibility in the allocation
of channel symbols. The resulting optimization problem, with a per-antenna
transmit power constraint, is solved by the Lagrange multiplier method and an
iterative algorithm is proposed
Continuously-implemented sliding-mode adaptive unknown-input observers under noisy measurements
International audienceWe propose an estimator for nonlinear systems with unmatched unknown inputs and under measurement noise. The estimator design is based on the combination of observer design for descriptor systems, sliding-modes theory and adaptive control. The estimation of the measurement noise is achieved thanks to the transformation of the original system into a singular form where the measurement noise makes part of the augmented state. Two adaptive parameters are updated online, one to compensate for the unknown bounds on the states, the unknown inputs and the measurement noise and a second one to compensate for the effect of the nonlinearities. To join robust state estimation and unknown-inputs reconstruction, our approach borrows inspiration from sliding-mode theory however, all signals are continuously implemented. We demonstrate that both state and unknown-inputs estimation are achieved up to arbitrarily small tolerance. The utility of our theoretical results is illustrated through simulation case-studies
- …