Carrier-phase synchronization can be approached in a
general manner by estimating the multiplicative distortion (MD) to which
a baseband received signal in an RF or coherent optical transmission
system is subjected. This paper presents a unified modeling and
estimation of the MD in finite-alphabet digital communication systems. A
simple form of MD is the camer phase exp GO) which has to be estimated
and compensated for in a coherent receiver. A more general case with
fading must, however, allow for amplitude as well as phase variations of
the MD.
We assume a state-variable model for the MD and generally obtain a
nonlinear estimation problem with additional randomly-varying system
parameters such as received signal power, frequency offset, and Doppler
spread. An extended Kalman filter is then applied as a near-OPTIMAL
solution to the adaptive MD and channel parameter estimation problem.
Examples are given to show the use and some advantages of this scheme.
Traveling Salesman Problem (TSP) has been an interesting problem for a long
time in classical optimization techniques which are based on linear and nonlinear
programming. TSP can be described as follows: Given a number of cities to visit
and their distances from all other cities know, an OPTIMAL travel route has to be
found so that each city is visited one and only once with the least possible distance
traveled. This is a simple problem with handful of cities but becomes complicated
as the number increases.
PRINCIPLE: PLS cross-validation using the SIMPLS or WIMPLS algorithm, respectively for tall or wide X-data. The OPTIMAL approach is selected automatically.
The combinatorial core of the OVSF code assignment problem
that arises in UMTS is to assign some nodes of a complete binary
tree of height h (the code tree) to n simultaneous connections, such that
no two assigned nodes (codes) are on the same root-to-leaf path. Each
connection requires a code on a specified level. The code can change over
time as long as it is still on the same level. We consider the one-step code
assignment problem: Given an assignment, move the minimum number of
codes to serve a new request. Minn and Siu proposed the so-called DCAalgorithm
to solve the problem OPTIMALly. We show that DCA does not
always return an OPTIMAL solution, and that the problem is NP-hard.
We give an exact nO(h)-time algorithm, and a polynomial time greedy
algorithm that achieves approximation ratio Θ(h). Finally, we consider
the online code assignment problem for which we derive several results
The basic principle using the branchand-
bound strategy to solve the traveling
salesperson optimization problem (TSP)
consists of two parts.
There is a way to split the solution space.
There is a way to predict a lower bound for a
class of solutions.
There is also a way to find an upper bound of
an OPTIMAL solution.
If the lower bound of a solution exceeds this
upper bound, this solution cannot be OPTIMAL.
Thus, we should terminate the branching
associated with this solution.
In this project we analyze and design the minimum mean-square error (MMSE) multiuser receiver for uniformly quantized synchronous code division multiple access (CDMA) signals in additive white Gaussian noise (AWGN) channels.This project is mainly based on the representation of uniform quantizer by gain plus additive noise model. Based on this model, we derive the weight vector and the output signal-to-interference ratio (SIR) of the MMSE receiver. The effects of quantization on the MMSE receiver performance is characterized in a single parameter named 鈥漞quivalent noise variance鈥? The OPTIMAL quantizer stepsize which maximizes the MMSE receiver output SNR is also determined.
In an electromagnetic cloak based on a transformation approach, reduced sets of
material properties are generally favored due to their easier implementation in reality,
although a seemingly inevitable drawback of undesired reflection exists in such cloaks.
Here we suggest using high-order transformations to create smooth moduli at the outer
boundary of the cloak, therefore completely eliminating the detrimental scattering
within the limit of geometric optics. We apply this scheme to a non-magnetic
cylindrical cloak and demonstrate that the scattered field is reduced substantially in a
cloak with OPTIMAL quadratic transformation as compared to its linear counterpart.
OTSU Gray-level image segmentation using Otsu s method.
Iseg = OTSU(I,n) computes a segmented image (Iseg) containing n classes
by means of Otsu s n-thresholding method (Otsu N, A Threshold Selection
Method from Gray-Level Histograms, IEEE Trans. Syst. Man Cybern.
9:62-66 1979). Thresholds are computed to maximize a separability
criterion of the resultant classes in gray levels.
OTSU(I) is equivalent to OTSU(I,2). By default, n=2 and the
corresponding Iseg is therefore a binary image. The pixel values for
Iseg are [0 1] if n=2, [0 0.5 1] if n=3, [0 0.333 0.666 1] if n=4, ...
[Iseg,sep] = OTSU(I,n) returns the value (sep) of the separability
criterion within the range [0 1]. Zero is obtained only with images
having less than n gray level, whereas one (OPTIMAL value) is obtained
only with n-valued images.
WSNs being energy constrained systems, one major problem is to employ the sensor nodes in such a manner so as to ensure maximum coverage and connectivity with minimal or OPTIMAL number of nodes and furthermore elongate network lifetime with maximum energy utilization.
The problem addressed has been tackled for 1-D linear array and further extended to 2-Dimensions as stated in the next slides.
Traveling Salesperson Problem
Our branch-and-strategy splits a branch and bound solution into two groups:
one group including a particular arc and the other excluding this arc.
1.Each splitting incurs a lower bound and we shall traverse the searching tree with the "lower" lower bound.
2.If a constant subtracted from any row
or any column of the cost matrix, an
OPTIMAL solution does not change.
