207,097 research outputs found
Aspects of real-time digital spectral analysis
In the field of control engineering there is
a need
to
study
the dynamic behaviour
of systems which are subjected
to
random
disturbances. A technique
which
is
of great practical use
is to
describe the dynamic
properties as a
function
of
frequency. This
involves determining the frequency content, or spectrum, of
the
disturbances,
and
the frequency
response
function
of
the
system.
There
are many analogue and digital techniques which are designed for this
type
of spectral analysis.
However, digital computer
techniques
are
often avoided because they
are slow, and data must
be
collected
'off-line'.
A
recently
discovered
computational method,
termed the fast-
Fourier-transform (FFT),
enables
digital
spectral analysis
to be
carried-
out in
a much shorter
time than
was previously possible.
In
view of
this discovery it
was
decided to develop digital computer programmes
which would overcome
the disadvantages
of conventional
digital
spectral
analysis. Using these
programmes a computer would
be
connected, via
an analogue
to digital interface, to the
signal source, and would process
the data
as
it
entered
the
computer.
In the jargon
of computing,
the
computer would
be 'on-line'
and analyzing
the
spectra
in 'real-time'.
The first
part of
the
project consisted of an
investigation
of
the FFP
when programmed
for an on-line
digital
computer.
The
results of
this investigation
showed
that
a rapid, accurate, and compact
FFT
could be
programmed
by
using
fixed-point
arithmetic, and coding
in
an assembly language. The
speed of
the transform
was sufficient
to
allow spectral analysis over a
frequency
range useful
in
control
applications.
Two
on-line computer programmes
based upon
the YPP were
then
written; one
for 'real-time'
spectral analysis of a single record, and
another
for the 'real-time'
estimation of
the frequency
response
function
relating
two
signals.
In
order
that the
results of
these
programmes could
be
sensibly
interpreted, a statistical study was made
of
the
spectral estimators used
in the
programmes.
Arising from this
study, several contributions
to the field of
digital
spectra. analysis
were made.
These
were : -
1) A
more general covariance relationship
for cross-spectral
estimators.
2) An
examination of aliasing
in digital
spectral estimators.
3) Some theoretical
results concerning spectral estimators
for
closed loop
systems with random
disturbances inside the loop,
Some
experimental work was conducted with
the
real-time'
spectral analysis programmes, and it
was concluded
that the tec:
inique
is
more powerful
than
conventional
digital.
methods
because it is on-
line,
and can provide estimates with
improved
resolution and
statistical stability. Real-time digital
spectral analysis methods also
have the
advantage
that they
may
be
simply and quickly modified
to suit
specific applications
Rapid Frequency Estimation
Frequency estimation plays an important role in many digital signal processing applications. Many areas have benefited from the discovery of the Fast Fourier Transform (FFT) decades ago and from the relatively recent advances in modern spectral estimation techniques within the last few decades. As processor and programmable logic technologies advance, unconventional methods for rapid frequency estimation in white Gaussian noise should be considered for real time applications. In this thesis, a practical hardware implementation that combines two known frequency estimation techniques is presented, implemented, and characterized. The combined implementation, using the well known FFT and a less well known modern spectral analysis method known as the Direct State Space (DSS) algorithm, is used to demonstrate and promote application of modern spectral methods in various real time applications, including Electronic Counter Measure (ECM) techniques
Recovering galaxy star formation and metallicity histories from spectra using VESPA
We introduce VErsatile SPectral Analysis (VESPA): a new method which aims to
recover robust star formation and metallicity histories from galactic spectra.
VESPA uses the full spectral range to construct a galaxy history from synthetic
models. We investigate the use of an adaptative parametrization grid to recover
reliable star formation histories on a galaxy-by-galaxy basis. Our goal is
robustness as opposed to high resolution histories, and the method is designed
to return high time resolution only where the data demand it. In this paper we
detail the method and we present our findings when we apply VESPA to synthetic
and real Sloan Digital Sky Survey (SDSS) spectroscopic data. We show that the
number of parameters that can be recovered from a spectrum depends strongly on
the signal-to-noise, wavelength coverage and presence or absence of a young
population. For a typical SDSS sample of galaxies, we can normally recover
between 2 to 5 stellar populations. We find very good agreement between VESPA
and our previous analysis of the SDSS sample with MOPED.Comment: In press MNRAS, minor revisions to match accepted version by the
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Software algorithm and hardware design for real-time implementation of new spectral estimator
Background: Real-time spectral analyzers can be difficult to implement for PC computer-based systems because of the potential for high computational cost, and algorithm complexity. In this work a new spectral estimator (NSE) is developed for real-time analysis, and compared with the discrete Fourier transform (DFT). Method: Clinical data in the form of 216 fractionated atrial electrogram sequences were used as inputs. The sample rate for acquisition was 977 Hz, or approximately 1 millisecond between digital samples. Real-time NSE power spectra were generated for 16,384 consecutive data points. The same data sequences were used for spectral calculation using a radix-2 implementation of the DFT. The NSE algorithm was also developed for implementation as a real-time spectral analyzer electronic circuit board. Results: The average interval for a single real-time spectral calculation in software was 3.29 μs for NSE versus 504.5 μs for DFT. Thus for real-time spectral analysis, the NSE algorithm is approximately 150˟ faster than the DFT. Over a 1 millisecond sampling period, the NSE algorithm had the capability to spectrally analyze a maximum of 303 data channels, while the DFT algorithm could only analyze a single channel. Moreover, for the 8 second sequences, the NSE spectral resolution in the 3-12 Hz range was 0.037 Hz while the DFT spectral resolution was only 0.122 Hz. The NSE was also found to be implementable as a standalone spectral analyzer board using approximately 26 integrated circuits at a cost of approximately $500. The software files used for analysis are included as a supplement, please see the Additional files 1 and 2. Conclusions: The NSE real-time algorithm has low computational cost and complexity, and is implementable in both software and hardware for 1 millisecond updates of multichannel spectra. The algorithm may be helpful to guide radio frequency catheter ablation in real time
SSME propellant path leak detection real-time
Included are four documents that outline the technical aspects of the research performed on NASA Grant NAG8-140: 'A System for Sequential Step Detection with Application to Video Image Processing'; 'Leak Detection from the SSME Using Sequential Image Processing'; 'Digital Image Processor Specifications for Real-Time SSME Leak Detection'; and 'A Color Change Detection System for Video Signals with Applications to Spectral Analysis of Rocket Engine Plumes'
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