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368:, and the inverse of the estimates matrix is then used for finding estimated optimal weights.
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303:{\displaystyle {\hat {R}}_{X}={\frac {1}{K}}\sum \limits _{k=1}^{K}X_{k}X_{k}^{H},}
205:
correlation matrix of the array signals, may be obtained by means of a simple
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337:. The expression of the theoretically optimal weights requires the
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Widrow, B.; Mantey, P. E.; Griffiths, L. J.; Goode, B. B. (1967).
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145:{\displaystyle X_{1},X_{2},\dots ,X_{K}}
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27:that estimates weights of an array (
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1:
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445:Covariance and correlation
416:. Prentice Hall. pp.
380:"Adaptive antenna systems"
152:, an unbiased estimate of
198:{\displaystyle N\times N}
54:with its estimate. Using
388:Proceedings of the IEEE
21:direct matrix inversion
17:Sample matrix inversion
412:Adaptive Filter Theory
401:10.1109/proc.1967.6092
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361:{\displaystyle R_{X}}
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172:{\displaystyle R_{X}}
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93:-dimensional samples
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408:Haykin, S. (2002).
335:conjugate transpose
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31:) by replacing the
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33:correlation matrix
395:(12): 2143–2159.
326:{\displaystyle H}
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86:{\displaystyle N}
67:{\displaystyle K}
47:{\displaystyle R}
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29:adaptive filter
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450:Filter theory
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439:Categories
372:References
253:∑
227:^
207:averaging
190:×
127:…
25:algorithm
209:scheme:
23:) is an
339:inverse
333:is the
424:
420:–168.
313:where
179:, the
383:(PDF)
422:ISBN
19:(or
418:165
397:doi
341:of
441::
393:55
391:.
385:.
430:.
403:.
399::
354:X
350:R
321:H
298:,
293:H
288:k
284:X
278:k
274:X
268:K
263:1
260:=
257:k
247:K
244:1
239:=
234:X
224:R
193:N
187:N
165:X
161:R
138:K
134:X
130:,
124:,
119:2
115:X
111:,
106:1
102:X
81:N
62:K
42:R
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