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% RLS 算法
6 n; t$ }: i) Z+ J<br>randn('seed', 0) ;
) F( B3 t8 M: |( t" b o8 {+ _<br>rand('seed', 0) ;( V* M# W* M1 ^# P' G
<br>
& r7 }* F4 y% P- n<br>NoOfData = 8000 ; % Set no of data points used for training
. o4 a% e. I* }9 l! G% P. b<br>Order = 32 ; % Set the adaptive filter order/ I" B: }# r6 q
<br>
: i6 k. ^: n7 x3 \* o9 v6 l<br>Lambda = 0.98 ; % Set the forgetting factor
& n( K9 S; a( k<br>Delta = 0.001 ; % R initialized to Delta*I
- ] F3 p( N4 j9 J! }+ L9 K<br>7 N' [( k/ [- W, l2 B! t% B! j' p
<br>x = randn(NoOfData, 1) ;% Input assumed to be white: e* z; E. U3 L
<br>h = rand(Order, 1) ; % System picked randomly
9 o9 o2 V1 B0 s9 m I3 D2 B1 J% ~<br>d = filter(h, 1, x) ; % Generate output (desired signal)) l5 ]: A3 L, Q
<br>! ^& m6 h+ U; d; G7 l/ I9 F2 _
<br>% Initialize RLS
, Y: X8 ?4 H1 L<br>
( v& H5 b6 k' Y, Q Y<br>P = Delta * eye ( Order, Order ) ;
K: }5 m' F, d- m; F<br>w = zeros ( Order, 1 ) ;1 w+ S( m/ w) r9 W) t0 m
<br>8 e C# a, T- E: M6 L
<br>% RLS Adaptation
. r3 ^1 V9 t; M- |" e/ {1 C<br>
8 s5 {7 a5 H' T# N<br>for n = Order : NoOfData ;4 G; e) a. f4 a- q5 W) c: ~0 t( H
<br>
7 H( D- d) w/ {& M<br>u = x(n:-1:n-Order+1) ;
. @1 F) A( j6 V- j<br>pi_ = u' * P ;
; R' v7 T! x* n0 X& B; D<br>k = Lambda + pi_ * u ;
/ |7 e" V# }6 M2 [<br>K = pi_'/k;. y0 d0 g# F6 w
<br>e(n) = d(n) - w' * u ;
; B# W% X9 ^: G* m- m4 I<br>w = w + K * e(n) ;& q2 Z2 }( ]. W) R; K. u% ~
<br>PPrime = K * pi_ ;
+ h& S, ^. a" z8 Q- H<br>P = ( P - PPrime ) / Lambda ;$ a! p% R' O z8 x/ [
<br>w_err(n) = norm(h - w) ;
7 G5 a4 x5 ]- w* C! @<br>
2 U$ k$ z0 o3 ^$ n5 e/ b<br>end ;
' S+ y' P$ P6 w, v+ \& k7 m. {<br>
! i; R T, X. b0 l+ W* I' E- d- B) `<br>% Plot results- ~7 p! x8 M% L! N9 L7 Q
<br>
$ V4 ~- Z" ^" R2 E. z# g<br>figure ;0 V' R% x& a) R( w' w6 u
<br>plot(20*log10(abs(e))) ;
* L) V- J2 r/ y% c1 i<br>title('Learning Curve') ;7 g d+ y5 E& `- B
<br>xlabel('Iteration Number') ;
# v; \8 _, Z6 ]: V4 t<br>ylabel('Output Estimation Error in dB') ;# G5 [3 J" x: m! V- N
<br>
6 t2 V4 R$ k- f \2 ^4 S<br>figure ;! y7 J& @/ V7 S! ?4 ^
<br>semilogy(w_err) ;0 x _1 o j( L: _2 ~
<br>title('Weight Estimation Error') ;7 w' N' F! \# m* X% l& r+ o; {
<br>xlabel('Iteration Number') ;; T+ O& B4 p$ d
<br>ylabel('Weight Error in dB') ;# Y! |! E4 V* f& [8 y( ]! {
<br>' u% a3 e z7 }! O6 [) {$ G) Z; G
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发表于 2022-8-25 10:49
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