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Substitution of this pupil into Eqn. (6.64) leads immediately to Eqn. (6.83). Hopkins considers the defocus transfer function as a function of the wavefront curvature error w20 [120]. w20 is the distance between the actual focusing wavefront at the edge of the aperture and the wavefront that would focus without distortion at the image plane. The relationship between uz (1=zo 1=zi 1=F) and w20 is uz 2w20/A 2. Hopkins notation allows for similar consideration of diverse wavefront aberrations, such as spherical aberration, coma, and astigmatism. The defocus transfer function is displayed as a function of u and w20 for a circular aperture in Fig. 6.20. The OTF is cylindrically symmetric in the u, v plane for a circular aperture; Fig. 6.20 shows the cross section along a single axis. Hopkins [121] suggests that tolerable defocus at a given frequency u satis es j^w20 (u)j h ! 0:8 j^0 (u)j h (6:86)





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608 RA Iltis, JJ Shynk, and K Giridhar Recursive Bayesian algorithms for blind equalization In 25-th Asilomar Conference Signals, Systems Comp, pages 710 715 vol2 IEEE, 1991 609 RA Iltis, JJ Shynk, and K Giridhar Bayesian blind equalization for coded waveforms In Proc IEEE MILCOM, pages 211 215 vol1, San Diego, CA, 1992 610 RA Iltis, JJ Shynk, and K Giridhar Bayesian algorithms for blind equalization using parallel adaptive ltering IEEE Trans Communications, 42(2-4,):1017 1032, February 1994 611 T Inoue, Y Fujii, K Itoh, and Y Ichioka Block blind separation of independent spectra in hyperspectral-images In 1996 International Topical Meeting on Optical Computing Technical Digest, pages 40 41 vol1, Proceedings of International Topical Meeting on Optical Computing - OC 96, Sendai, Japan, 21-25 April 1996, 1996 Japan Society Appl Phys 612 Y Inouye.

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Blind deconvolution of multichannel linear time-invariant systems of non-minimum phase to appear in statistical methods in control and signal processing In T Katayama and S Sugimoto, editors, Statistical Methods in Control and Signal Processing New York: Marcel Dekker, 1997 613 Y Inouye Criteria for blind deconvolution of multichannel linear time-invariant systems of non-minimum phase In T Katayama and S Sugimoto, editors, Statistical Methods in Control and Signal Processing, pages 375 397 Dekker, New York, 1997 614 Y Inouye and T Habe Blind equalization of multichannel linear time invariant systems The Institute of Electronics Information and Communication Engineers, 24(24):9 16, 1995 615 Y Inouye and T Habe Multichannel blind equalization using second- and fourth-order cumulants In Proc IEEE Signal Processing Workshop on Higher Order Statistics, pages 96 100, 1995 616 Y Inouye and K Hirano.

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Blind identi cation of linear multi-input-multi-output systems driven by colored inputs with applications to blind signal separation In Proc IEEE Conference on Decision and Control, pages 715 720 vol1, New Orleans, LA, 1995 617 Y Inouye and S Ohno Adaptive algorithms for implementing the single-stage criterion for multichannel blind deconvolution In Proc of 5th Int Conference on Neural Information Processing, ICONIP 98, pages 733 736, Kitakyushu, Japan, October, 21-23 1998 618 Y Inouye and T Ohta Blind equalization of digital communication channels using fractionally spaced samples In Proc IEEE ISCAS, pages 165 168 vol2, Atlanta, GA, 1996 619 Y Inouye and T Sato Unconstrained optimization criteria for blind deconvolution of multichannel linear systems In S Amari, L Xu, L-W Chan, I King, and K-S Leung, editors, Progress in Neural Information Processing Proceedings of the International Conference on Neural Information Processing, pages 1189 1194 vol.

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