We address the problem of blind carrier frequency-offset (CFO) estimation in quadrature amplitude modulation,
phase-shift keying, and pulse amplitude modulation
communications systems.We study the performance of a standard
CFO estimate, which consists of first raising the received signal to
the Mth power, where M is an integer depending on the type and
size of the symbol constellation, and then applying the nonlinear
least squares (NLLS) estimation approach. At low signal-to noise
ratio (SNR), the NLLS method fails to provide an accurate CFO
estimate because of the presence of outliers. In this letter, we derive
an approximate closed-form expression for the outlier probability.
This enables us to predict the mean-square error (MSE) on CFO
estimation for all SNR values. For a given SNR, the new results
also give insight into the minimum number of samples required in
the CFO estimation procedure, in order to ensure that the MSE
on estimation is not significantly affected by the outliers.
In this paper, we consider the problem of filtering in relational
hidden Markov models. We present a compact representation for
such models and an associated logical particle filtering algorithm. Each
particle contains a logical formula that describes a set of states. The
algorithm updates the formulae as new observations are received. Since
a single particle tracks many states, this filter can be more accurate
than a traditional particle filter in high dimensional state spaces, as we
demonstrate in experiments.
The problem of image registration subsumes a number of problems and techniques in multiframe
image analysis, including the computation of optic flow (general pixel-based motion), stereo
correspondence, structure from motion, and feature tracking. We present a new registration
algorithm based on spline representations of the displacement field which can be specialized to
solve all of the above mentioned problems. In particular, we show how to compute local flow,
global (parametric) flow, rigid flow resulting from camera egomotion, and multiframe versions of
the above problems. Using a spline-based description of the flow removes the need for overlapping
correlation windows, and produces an explicit measure of the correlation between adjacent flow
estimates. We demonstrate our algorithm on multiframe image registration and the recovery of 3D
projective scene geometry. We also provide results on a number of standard motion sequences.
Solving Engineering Problems Using MATLAB C++ Math Library Introduction
In the previous article, we studied how can use MATLAB C API to solve engineering problems. In this article I will show you how can use MATLAB C++ math library. The MATLAB® C++ Math Library serves two separate constituencies: MATLAB programmers seeking more speed or complete independence from interpreted MATLAB, and C++ programmers who need a fast, easy-to-use matrix math library. To each, it offers distinct advantages.
