228 research outputs found
Lecture notes on the design of low-pass digital filters with wireless-communication applications
The low-pass filter is a fundamental building block from which digital
signal-processing systems (e.g. radio and radar) are built. Signals in the
electromagnetic spectrum extend over all timescales/frequencies and are used to
transmit and receive very long or very short pulses of very narrow or very wide
bandwidth. Time/Frequency agility is the key for optimal spectrum utilization
(i.e. to suppress interference and enhance propagation) and low-pass filtering
is the low-level digital mechanism for manoeuvre in this domain. By increasing
and decreasing the bandwidth of a low-pass filter, thus decreasing and
increasing its pulse duration, the engineer may shift energy concentration
between frequency and time. Simple processes for engineering such components
are described and explained below. These lecture notes are part of a short
course that is intended to help recent engineering graduates design low-pass
digital filters for this purpose, who have had some exposure to the topic
during their studies, and who are now interested in the sending and receiving
signals over the electromagnetic spectrum, in wireless communication (i.e.
radio) and remote sensing (e.g. radar) applications, for instance. The best way
to understand the material is to interact with the spectrum using receivers and
or transmitters and software-defined radio development-kits provide a
convenient platform for experimentation. Fortunately, wireless communication in
the radio-frequency spectrum is an ideal application for the illustration of
waveform agility in the electromagnetic spectrum. In Parts I and II, the
theoretical foundations of digital low-pass filters are presented, i.e.
signals-and-systems theory, then in Part III they are applied to the problem of
radio communication and used to concentrate energy in time or frequency.Comment: Added Slepian ref. Added arXiv ID to heade
Improved IIR Low-Pass Smoothers and Differentiators with Tunable Delay
Regression analysis using orthogonal polynomials in the time domain is used
to derive closed-form expressions for causal and non-causal filters with an
infinite impulse response (IIR) and a maximally-flat magnitude and delay
response. The phase response of the resulting low-order smoothers and
differentiators, with low-pass characteristics, may be tuned to yield the
desired delay in the pass band or for zero gain at the Nyquist frequency. The
filter response is improved when the shape of the exponential weighting
function is modified and discrete associated Laguerre polynomials are used in
the analysis. As an illustrative example, the derivative filters are used to
generate an optical-flow field and to detect moving ground targets, in real
video data collected from an airborne platform with an electro-optic sensor.Comment: To appear in Proc. International Conference on Digital Image
Computing: Techniques and Applications (DICTA), Adelaide, 23rd-25th Nov. 201
Parallel software implementation of recursive multidimensional digital filters for point-target detection in cluttered infrared scenes
A technique for the enhancement of point targets in clutter is described. The
local 3-D spectrum at each pixel is estimated recursively. An optical
flow-field for the textured background is then generated using the 3-D
autocorrelation function and the local velocity estimates are used to apply
high-pass velocity-selective spatiotemporal filters, with finite impulse
responses (FIRs), to subtract the background clutter signal, leaving the
foreground target signal, plus noise. Parallel software implementations using a
multicore central processing unit (CPU) and a graphical processing unit (GPU)
are investigated.Comment: To appear in Proc. 2015 IEEE International Conference on Acoustics,
Speech and Signal Processing (ICASSP). Added header and DO
Mnemonic function in small vessel disease and associations with white matter tract microstructure.
Cerebral small vessel disease (SVD) is associated with deficits in working memory, with a relative sparing of long-term memory; function may be influenced by white matter microstructure. Working and long-term memory were examined in 106 patients with SVD and 35 healthy controls. Microstructure was measured in the uncinate fasciculi and cingula. Working memory was more impaired than long-term memory in SVD, but both abilities were reduced compared to controls. Regression analyses found that having SVD explained the variance in memory functions, with additional variance explained by the cingula (working memory) and uncinate (long-term memory). Performance can be explained in terms of integrity loss in specific white matter tract associated with mnemonic functions
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