Abstract:
The thesis is divided in three parts. In the rst part, it explores and discusses
the diversity of concepts and motivations for obtaining good resolution and highly
concentrated time–frequency distributions (TFDs) for the research community. The
description of the methods used for TFDs' objective assessment is provided later in
this part.
In the second part, a novel multi–processes ANN based framework to obtain
highly concentrated TFDs is proposed. The propose method utilizes a localised Bayesian
regularised neural network model (BRNNM) to obtain the energy concentration along
the instantaneous frequencies (IFs) of individual components in the multicomponent
signals without assuming any prior knowledge. The spectrogram and pre–processed
Wigner–Ville distribution (WD) of the signals with known IF laws are used as the train-
ing set for the BRNNM. These distributions, taken as two–dimensional (2–D) image
matrices, are vectorized and clustered according to the elbow criterion. Each cluster
contains the pairs of the input and target vectors from the spectrograms and highly
concentrated pre–processed WD respectively. For each cluster, the pairs of vectors are
used to train the multiple ANNs under the Bayesian framework of David Mackay. The
best trained network for each cluster is selected based on network error criterion. In
the test phase, the test TFDs of unknown signals, after vectorization and clustering,
are processed through these specialized ANNs. After post–processing, the resultingTFDs are found to exhibit improved resolution and concentration along the individual
components then the initial blurred estimates.
The third part presents the discussion on the experimental results obtained by the
proposed technique. Moreover the framework is extended to include the various objec-
tive methods of assessment to evaluate the performance of de–blurred TFDs obtained
through the proposed technique. The selected methods not only allow quantifying the
quality of TFDs instead of relying solely on visual inspection of their plots, but also
help in drawing comparison of the proposed technique with the other existing tech-
niques found in literature for the purpose. In particular the computation regularities
show the effectiveness of the objective criteria in quantifying the TFDs' concentration
and resolution information.