DocumentCode :
2761228
Title :
Digital Signal Processing Without Arithmetic Using Regression Trees
Author :
Gunther, Jake ; Moon, Todd
Author_Institution :
Dept. of Electr. & Comput. Eng., Utah State Univ., Logan, UT
fYear :
2009
fDate :
4-7 Jan. 2009
Firstpage :
524
Lastpage :
529
Abstract :
This paper discusses the possibility of performing digital signal processing tasks such as filtering without doing arithmetic, i. e. addition and multiplication, by relying on the approximating capabilities of regression trees. Regression trees map a vector of inputs to a scalar output using only comparison (greater than, less than) operations. Therefore, regression trees can approximate the value of a given function without doing arithmetic offering a computational savings. This paper demonstrates the performance of regression trees on simple FIR filtering problems.
Keywords :
FIR filters; digital signal processing chips; filtering theory; regression analysis; FIR filtering problems; digital signal processing; filtering; regression trees map; Application specific integrated circuits; Cost function; Digital arithmetic; Digital filters; Digital signal processing; Filtering; Finite impulse response filter; Moon; Nonlinear filters; Regression tree analysis; finite impulse response filter; regression tree;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Digital Signal Processing Workshop and 5th IEEE Signal Processing Education Workshop, 2009. DSP/SPE 2009. IEEE 13th
Conference_Location :
Marco Island, FL
Print_ISBN :
978-1-4244-3677-4
Electronic_ISBN :
978-1-4244-3677-4
Type :
conf
DOI :
10.1109/DSP.2009.4785979
Filename :
4785979
Link To Document :
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