Results 231 to 240 of about 2,652,813 (292)

Beyond CT: Attenuation correction for stand-alone brain PET. [PDF]

open access: yesZ Med Phys
Jehl M   +6 more
europepmc   +1 more source

Allometry correction in semi-quantitative analysis of dopamine transporter SPECT. [PDF]

open access: yesEJNMMI Res
Buddenkotte T   +3 more
europepmc   +1 more source

An Affine Projection Algorithm With Evolving Order

open access: yesIEEE Signal Processing Letters, 2009
We present a novel affine projection algorithm (APA) which automatically determines its projection order by an evolutionary method. The evolutionary method increases or decreases the projection order by comparing the output error with a threshold. The experimental results show that the proposed algorithm has fast convergence speed and small steady ...
Seong-Eun Kim, Woo-Jin Song
exaly   +5 more sources

Affine projection algorithm with selective projections

open access: yesSignal Processing, 2012
In the affine projection adaptive filtering algorithm, convergence is sped up by increasing the projection order but with an unwelcome consequence of increased steady-state misalignment. To address this unfavorable compromise, we propose a new affine projection algorithm with selective projections. This algorithm adaptively changes the projection order
Reza Arablouei, Kutluyil Dogancay
exaly   +3 more sources

Affine projection algorithm with variable projection order

open access: yes2012 IEEE International Conference on Communications (ICC), 2012
Increasing the projection order in the affine projection adaptive filtering algorithm speeds up the convergence but also increases the steady-state misalignment. To address this unfavorable compromise, we propose a new affine projection algorithm with a variable projection order.
Reza Arablouei, Kutluyil Dogançay
openaire   +2 more sources

Set-membership affine projection algorithm

IEEE Signal Processing Letters, 2001
This letter presents a new data selective adaptive filtering algorithm, the set-membership affine projection (SM-AP) algorithm. The algorithm generalizes the idea of the set-membership NLMS (SM-NLMS) algorithm to include constraint sets constructed from the past input and desired signal pairs.
Stefan Werner, P S R Diniz
exaly   +2 more sources

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