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Hsia, and BG Agee Interference rejection using the timedependent constant modulus algorithm (CMA) and the hybrid CMA/spectral correlation discriminator IEEE Trans Signal Processing, 39(9):2108 2111, September 1991 846 Y Meng, K-M Wong, and K Lazaris-Brunner An improved cyclic adaptive beamforming (CAB) algorithm for a multiple agile beam mobile communication system In Proc IEEE SP Workshop on Stat Signal Array Processing, pages 148 151, Corfu, Greece, 1996 847 H Messer and Y Bar-Ness Bootstrapped spatial separation of wideband superimposed signals In Signal Processing VI: Theories and Applications, pages 819 822 Elsevier, 1992 848 Y Miao and Y Hua Fast subspace tracking and neural network learning by a novel information criterion IEEE Trans on Signal Processing, 46(7):1967 1979, 1998 849 MJ Minardi and MA Ingram Finding misconvergences in blind equalizers and new variance constraint cost functions to mitigate the problem In Proc IEEE ICASSP, pages 1723 1726 vol.

ri). The Cox distribution is visualised in Figure 3.12 where the small black indicate the probabilistic choices to be made before each exponential phase. coefficients of variation both smaller and larger than

3, Atlanta, GA, 1996 850 N Miura and N Baba Extended-object reconstruction with sequential use of the iterative blind deconvolution method Optics Communications, 89(5-6):375 379, May 1992 851 N Miura and N Baba Segmentation-based multiframe blind deconvolution of solar images Journal of the Optical Society of America A (Optics, Image Science and Vision), 12(9):1858 1866, September 1995..

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Proof: Let dim(U) = 7 n ,dim(V) = 11, and &. Bt. some bases in the spaces U and V , be respectively. By Lemma A.l 1 every L 6 C(U. V )can be represented by an 71 x m matrix A f I , SO that

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Stationary Environments 1. Consider adaptive filters that are described by stochastic difference equations of the form

Reuse the four-state CTMC of the previous exercise and assume that p(O) = (l,O, 0,O). Compute the transient probability distribution for t = 1 using the following methods: 1. The RK4-method 2. The uniformisation (how large should h be ). method, thereby also addressing rate A n = 1,2,3,4,5 the following questions:

Having talked a lot about process, how about outcomes Where do you want to end up Should there be a consensus outcome or is residual con ict acceptable Again, there is more than one way to evaluate a successful negotiation. Apart from the direct bene ts, other gains are important as well. A special think tank on negotiation at Harvard Law School called the Program on Negotiation (PON) has carried out a lot of research over the past 15 years or so to look at the questions: What is a successful negotiation and What kinds of strategies and behaviors lead to success This research has involved watching people role-play different kinds of negotiations encouraging them to adopt rst one approach and then the other and watching the results: Satisfying outcome: Even if the deal is not terri c for you, if it is better than anything else you might have received elsewhere, then the outcome can and probably should be considered successful . Sustainability: The agreement is only likely to last if negotiating partners can live with it. Acceptable cost: If you spent much longer negotiating than you had time for, or expended more resources than your organisation could afford, the settlement reached is not ef cient.

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18.0 Summary ....................................................................... 18.1 Introduction .......................................................................... 18.2 Formulation of a Direct Data Domain Least Squares Method for Adaptive Processing of Finite Bandwidth Signals Having Different Frequencies .................................. 18.2.1 Forward Method for Adaptive Processing of Broadband Signals .................................................. 18.2.2 Backward Method .................................................. 18.2.3 Forward-Backward Method .................................... 18.3 Numerical Simulation Results .............................................. 18.4 Conclusion ............................................................................ References ............................................................................

varied statistical conditions on the data. We shall see in Parts IV (Mean-Square Performance) and V (Transient Pe$ormance) that this is indeed the case - see, e.g., Sec. 21.5.

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