B. Alberts, D. Bray, J. Lewis, M. Raff, K. Roberts, and J. Watson, Molecular Biology of the Cell (Garland, New York, 1989).

C. An, L. Petrovic, and A. Marchevsky, “The application of image analysis and neural network technology to the study of large cell liver cells,” Hepatocell Carcin. 26, 1224–2230 (1997).

S. Shiotani, T. Fukuda, and F. Arai, “Cell recognition by image processing (recognition of dead or living plant cells by neural network),” JSME Int. J. Ser. C 371, 233–240 (1994).

M. Astion and P. Wilding, “The application of backpropagation neural networks to problems in pathology,” Arch. Pathol. Lab. Med. 116, 995–1001 (1992).

[PubMed]

S. Lawrence, C. Lee Giles, A. C. Tsoi, and A. Back, “Face recognition: a convolutional neural-network approach,” IEEE Trans. Neural Networks 8, 98–113 (1997).

[CrossRef]

H. Lodish, D. Baltimore, A. Berk, S. Zipursky, P. Matsudaira, and J. Darnell, Molecular Cell Biology (Scientific American, New York, 1995).

H. Lodish, D. Baltimore, A. Berk, S. Zipursky, P. Matsudaira, and J. Darnell, Molecular Cell Biology (Scientific American, New York, 1995).

D. Beymer and T. Poggio, “Image representations for visual learning,” Science 272, 1905–1909 (1996).

[CrossRef]
[PubMed]

C. Bishop, Neural Networks for Statistical Pattern Recognition (Oxford U. Press, Oxford, 1994).

J. Blue, G. Candela, P. Grother, R. Chellapa, and C. Wilson, “Evaluation of pattern classifiers for fingerprint and OCR applications,” Patt. Recog. 27, 485–501 (1994).

[CrossRef]

L. Bottou, C. Cortes, J. Denker, H. Drucker, I. Guyon, L. Jackel, Y. Le Cun, U. Muller, E. Sackinger, P. Simard, and V. Vapnik, “Comparison of classifier methods: a case study in handwritten digit recognition,” in Proceedings of the International Conference on Pattern Recognition (IEEE Comput. Soc. Press, Los Alamitos, Calif., 1994), Vol. 2, pp. 77–82.

B. Alberts, D. Bray, J. Lewis, M. Raff, K. Roberts, and J. Watson, Molecular Biology of the Cell (Garland, New York, 1989).

M. Brickley, J. Coupe, and J. Shepherd, “Performance of a computer-simulated neural network trained to categorize normal, premalignant and malignant oral smears,” J. Oral Pathol. Med. 25, 424–430 (1996).

[CrossRef]
[PubMed]

D. Burton, “Text-dependent speaker verification using vector quantization source coding,” IEEE Trans. Acoust. Speech Signal Process. ASSP-35, 133–140 (1987).

[CrossRef]

J. Blue, G. Candela, P. Grother, R. Chellapa, and C. Wilson, “Evaluation of pattern classifiers for fingerprint and OCR applications,” Patt. Recog. 27, 485–501 (1994).

[CrossRef]

J. Chamberlain, The Principles of Interferometric Spectroscopy (Wiley, New York, 1979), Chap. 9.

R. Chellapa, C. Wilson, and S. Sirohey, “Human and machine recognition of faces,” Proc. IEEE 83, 705–740 (1995).

[CrossRef]

J. Blue, G. Candela, P. Grother, R. Chellapa, and C. Wilson, “Evaluation of pattern classifiers for fingerprint and OCR applications,” Patt. Recog. 27, 485–501 (1994).

[CrossRef]

L. Bottou, C. Cortes, J. Denker, H. Drucker, I. Guyon, L. Jackel, Y. Le Cun, U. Muller, E. Sackinger, P. Simard, and V. Vapnik, “Comparison of classifier methods: a case study in handwritten digit recognition,” in Proceedings of the International Conference on Pattern Recognition (IEEE Comput. Soc. Press, Los Alamitos, Calif., 1994), Vol. 2, pp. 77–82.

F. Tsung and G. Cottrell, “Learning in recurrent finite difference networks,” Int. J. Neural Sys. 6, 249–255 (1995).

[CrossRef]

M. Brickley, J. Coupe, and J. Shepherd, “Performance of a computer-simulated neural network trained to categorize normal, premalignant and malignant oral smears,” J. Oral Pathol. Med. 25, 424–430 (1996).

[CrossRef]
[PubMed]

I. Cox, J. Ghosn, and P. Yianilos, “Feature-based face recognition using mixture–distance,” in Computer Vision and Pattern Recognition (IEEE Press, Piscataway, N.J., 1996).

H. Lodish, D. Baltimore, A. Berk, S. Zipursky, P. Matsudaira, and J. Darnell, Molecular Cell Biology (Scientific American, New York, 1995).

L. Bottou, C. Cortes, J. Denker, H. Drucker, I. Guyon, L. Jackel, Y. Le Cun, U. Muller, E. Sackinger, P. Simard, and V. Vapnik, “Comparison of classifier methods: a case study in handwritten digit recognition,” in Proceedings of the International Conference on Pattern Recognition (IEEE Comput. Soc. Press, Los Alamitos, Calif., 1994), Vol. 2, pp. 77–82.

L. Bottou, C. Cortes, J. Denker, H. Drucker, I. Guyon, L. Jackel, Y. Le Cun, U. Muller, E. Sackinger, P. Simard, and V. Vapnik, “Comparison of classifier methods: a case study in handwritten digit recognition,” in Proceedings of the International Conference on Pattern Recognition (IEEE Comput. Soc. Press, Los Alamitos, Calif., 1994), Vol. 2, pp. 77–82.

W. Press, S. Teukolsky, W. Vetterling, and B. Flannery, Numerical Recipes in C—The Art of Scientific Computing, 2nd ed. (Cambridge U. Press, New York, 1992).

S. Shiotani, T. Fukuda, and F. Arai, “Cell recognition by image processing (recognition of dead or living plant cells by neural network),” JSME Int. J. Ser. C 371, 233–240 (1994).

K. Fukunaga, Introduction to Statistical Pattern Recognition, 2nd ed. (Macmillan, New York, 1990).

K. Fukunaga and J. Young, “Pattern recognition and neural engineering,” in Neural Networks, Concepts, Applications and Implementations, P. Antognetti and V. Milutinovic, eds. (Prentice Hall, EngleWood Cliffs, N.J., 1991), Vol. 1, pp. 10–33.

I. Cox, J. Ghosn, and P. Yianilos, “Feature-based face recognition using mixture–distance,” in Computer Vision and Pattern Recognition (IEEE Press, Piscataway, N.J., 1996).

S. Lawrence, C. Lee Giles, A. C. Tsoi, and A. Back, “Face recognition: a convolutional neural-network approach,” IEEE Trans. Neural Networks 8, 98–113 (1997).

[CrossRef]

R. Gonzalez and R. Woods, Digital Image Processing (Addison-Wesley, New York, 1993).

J. Tou and R. Gonzalez, Pattern Recognition Principles (Addison-Wesley, London, 1974).

J. Blue, G. Candela, P. Grother, R. Chellapa, and C. Wilson, “Evaluation of pattern classifiers for fingerprint and OCR applications,” Patt. Recog. 27, 485–501 (1994).

[CrossRef]

L. Gupta, R. Mohammed, and R. Tammana, “A neural network approach to robust shape classification,” Pattern Recog. 23, 563–568 (1990).

[CrossRef]

L. Bottou, C. Cortes, J. Denker, H. Drucker, I. Guyon, L. Jackel, Y. Le Cun, U. Muller, E. Sackinger, P. Simard, and V. Vapnik, “Comparison of classifier methods: a case study in handwritten digit recognition,” in Proceedings of the International Conference on Pattern Recognition (IEEE Comput. Soc. Press, Los Alamitos, Calif., 1994), Vol. 2, pp. 77–82.

S. Haykin, Neural Network—A Comprehensive Foundation (Macmillan, New York, 1994).

Y. Qi and B. Hunt, “Signature verification using global and grid features,” Patt. Recog. 27, 1621–1629 (1994).

[CrossRef]

M. McCord Nelson, and W. Illington, A Practical Guide to Neural Nets (Addison-Wesley, Reading, Mass., 1991).

S. Inoue, Video Microscopy (Plenum, New York, 1986).

L. Bottou, C. Cortes, J. Denker, H. Drucker, I. Guyon, L. Jackel, Y. Le Cun, U. Muller, E. Sackinger, P. Simard, and V. Vapnik, “Comparison of classifier methods: a case study in handwritten digit recognition,” in Proceedings of the International Conference on Pattern Recognition (IEEE Comput. Soc. Press, Los Alamitos, Calif., 1994), Vol. 2, pp. 77–82.

A. Jain and J. Mao, “Guest editorial: special issue on artificial neural networks and statistical pattern recognition,” IEEE Trans. Neural Networks 8, 1–3 (1997).

[CrossRef]

S. Lawrence, C. Lee Giles, A. C. Tsoi, and A. Back, “Face recognition: a convolutional neural-network approach,” IEEE Trans. Neural Networks 8, 98–113 (1997).

[CrossRef]

L. Bottou, C. Cortes, J. Denker, H. Drucker, I. Guyon, L. Jackel, Y. Le Cun, U. Muller, E. Sackinger, P. Simard, and V. Vapnik, “Comparison of classifier methods: a case study in handwritten digit recognition,” in Proceedings of the International Conference on Pattern Recognition (IEEE Comput. Soc. Press, Los Alamitos, Calif., 1994), Vol. 2, pp. 77–82.

L. Levi, Applied Optics—A Guide to Optical System Design (Wiley, New York, 1968), Vol. 1, pp. 152–154.

B. Alberts, D. Bray, J. Lewis, M. Raff, K. Roberts, and J. Watson, Molecular Biology of the Cell (Garland, New York, 1989).

H. Lodish, D. Baltimore, A. Berk, S. Zipursky, P. Matsudaira, and J. Darnell, Molecular Cell Biology (Scientific American, New York, 1995).

L. Mango, “Deducing false negatives in clinical practice: the role of neural network technology,” Am. J. Obstetr. Gynecol. 175, 1114–1119 (1996).

[CrossRef]

D. Rosenthal and L. Mango, “Applications of neural networks for interactive diagnosis of anatomic pathology specimens,” in Compendium on the Computerized Cytology and Histology Laboratory, Tutorials of Cytology, G. Weid, P. Bartels, D. Rosenthal, and U. Schenck, eds. (Karger, Chicago, 1994), pp. 173–184.

J. Proakis and D. Manolakis, Digital Signal Processing—Principles, Algorithm, and Applications, 2nd ed. (Macmillan, New York, 1992), pp. 41–43.

A. Jain and J. Mao, “Guest editorial: special issue on artificial neural networks and statistical pattern recognition,” IEEE Trans. Neural Networks 8, 1–3 (1997).

[CrossRef]

C. An, L. Petrovic, and A. Marchevsky, “The application of image analysis and neural network technology to the study of large cell liver cells,” Hepatocell Carcin. 26, 1224–2230 (1997).

T. Masters, Signal and Image Processing With Neural Networks (Wiley, New York, 1993).

H. Lodish, D. Baltimore, A. Berk, S. Zipursky, P. Matsudaira, and J. Darnell, Molecular Cell Biology (Scientific American, New York, 1995).

L. Gupta, R. Mohammed, and R. Tammana, “A neural network approach to robust shape classification,” Pattern Recog. 23, 563–568 (1990).

[CrossRef]

L. Bottou, C. Cortes, J. Denker, H. Drucker, I. Guyon, L. Jackel, Y. Le Cun, U. Muller, E. Sackinger, P. Simard, and V. Vapnik, “Comparison of classifier methods: a case study in handwritten digit recognition,” in Proceedings of the International Conference on Pattern Recognition (IEEE Comput. Soc. Press, Los Alamitos, Calif., 1994), Vol. 2, pp. 77–82.

M. McCord Nelson, and W. Illington, A Practical Guide to Neural Nets (Addison-Wesley, Reading, Mass., 1991).

A. Papoulis, Probability, Random Variables, and Stochastic Processes, 2nd ed. (McGraw-Hill, New York, 1984).

G. Parry, “Speckle patterns in partially coherent light,” in Laser Speckle and Related Phenomena, Vol. 9 of Topics in Applied Physics Series (Springer-Verlag, Berlin, 1984).

C. An, L. Petrovic, and A. Marchevsky, “The application of image analysis and neural network technology to the study of large cell liver cells,” Hepatocell Carcin. 26, 1224–2230 (1997).

D. Beymer and T. Poggio, “Image representations for visual learning,” Science 272, 1905–1909 (1996).

[CrossRef]
[PubMed]

W. Press, S. Teukolsky, W. Vetterling, and B. Flannery, Numerical Recipes in C—The Art of Scientific Computing, 2nd ed. (Cambridge U. Press, New York, 1992).

J. Proakis and D. Manolakis, Digital Signal Processing—Principles, Algorithm, and Applications, 2nd ed. (Macmillan, New York, 1992), pp. 41–43.

Y. Qi and B. Hunt, “Signature verification using global and grid features,” Patt. Recog. 27, 1621–1629 (1994).

[CrossRef]

B. Alberts, D. Bray, J. Lewis, M. Raff, K. Roberts, and J. Watson, Molecular Biology of the Cell (Garland, New York, 1989).

T. Watkin and A. Rau, “The statistical mechanics of learning a rule,” Rev. Mod. Phys. 65, 499–556 (1994).

[CrossRef]

B. Alberts, D. Bray, J. Lewis, M. Raff, K. Roberts, and J. Watson, Molecular Biology of the Cell (Garland, New York, 1989).

D. Rosenthal and L. Mango, “Applications of neural networks for interactive diagnosis of anatomic pathology specimens,” in Compendium on the Computerized Cytology and Histology Laboratory, Tutorials of Cytology, G. Weid, P. Bartels, D. Rosenthal, and U. Schenck, eds. (Karger, Chicago, 1994), pp. 173–184.

L. Bottou, C. Cortes, J. Denker, H. Drucker, I. Guyon, L. Jackel, Y. Le Cun, U. Muller, E. Sackinger, P. Simard, and V. Vapnik, “Comparison of classifier methods: a case study in handwritten digit recognition,” in Proceedings of the International Conference on Pattern Recognition (IEEE Comput. Soc. Press, Los Alamitos, Calif., 1994), Vol. 2, pp. 77–82.

T. Sanger, “Optimal unsupervised learning in a single-layer linear feed forward neural network,” Neural Networks 2, 459–473 (1989).

[CrossRef]

M. Brickley, J. Coupe, and J. Shepherd, “Performance of a computer-simulated neural network trained to categorize normal, premalignant and malignant oral smears,” J. Oral Pathol. Med. 25, 424–430 (1996).

[CrossRef]
[PubMed]

S. Shiotani, T. Fukuda, and F. Arai, “Cell recognition by image processing (recognition of dead or living plant cells by neural network),” JSME Int. J. Ser. C 371, 233–240 (1994).

L. Bottou, C. Cortes, J. Denker, H. Drucker, I. Guyon, L. Jackel, Y. Le Cun, U. Muller, E. Sackinger, P. Simard, and V. Vapnik, “Comparison of classifier methods: a case study in handwritten digit recognition,” in Proceedings of the International Conference on Pattern Recognition (IEEE Comput. Soc. Press, Los Alamitos, Calif., 1994), Vol. 2, pp. 77–82.

R. Chellapa, C. Wilson, and S. Sirohey, “Human and machine recognition of faces,” Proc. IEEE 83, 705–740 (1995).

[CrossRef]

M. Soriano and C. Saloma, “Cell classification by a learning principal components analyzer and a backpropagation neural network,” Bioimaging 3, 168–175 (1995).

[CrossRef]

L. Gupta, R. Mohammed, and R. Tammana, “A neural network approach to robust shape classification,” Pattern Recog. 23, 563–568 (1990).

[CrossRef]

W. Press, S. Teukolsky, W. Vetterling, and B. Flannery, Numerical Recipes in C—The Art of Scientific Computing, 2nd ed. (Cambridge U. Press, New York, 1992).

J. Tou and R. Gonzalez, Pattern Recognition Principles (Addison-Wesley, London, 1974).

S. Lawrence, C. Lee Giles, A. C. Tsoi, and A. Back, “Face recognition: a convolutional neural-network approach,” IEEE Trans. Neural Networks 8, 98–113 (1997).

[CrossRef]

F. Tsung and G. Cottrell, “Learning in recurrent finite difference networks,” Int. J. Neural Sys. 6, 249–255 (1995).

[CrossRef]

L. Bottou, C. Cortes, J. Denker, H. Drucker, I. Guyon, L. Jackel, Y. Le Cun, U. Muller, E. Sackinger, P. Simard, and V. Vapnik, “Comparison of classifier methods: a case study in handwritten digit recognition,” in Proceedings of the International Conference on Pattern Recognition (IEEE Comput. Soc. Press, Los Alamitos, Calif., 1994), Vol. 2, pp. 77–82.

W. Press, S. Teukolsky, W. Vetterling, and B. Flannery, Numerical Recipes in C—The Art of Scientific Computing, 2nd ed. (Cambridge U. Press, New York, 1992).

T. Watkin and A. Rau, “The statistical mechanics of learning a rule,” Rev. Mod. Phys. 65, 499–556 (1994).

[CrossRef]

B. Alberts, D. Bray, J. Lewis, M. Raff, K. Roberts, and J. Watson, Molecular Biology of the Cell (Garland, New York, 1989).

M. Astion and P. Wilding, “The application of backpropagation neural networks to problems in pathology,” Arch. Pathol. Lab. Med. 116, 995–1001 (1992).

[PubMed]

R. Chellapa, C. Wilson, and S. Sirohey, “Human and machine recognition of faces,” Proc. IEEE 83, 705–740 (1995).

[CrossRef]

J. Blue, G. Candela, P. Grother, R. Chellapa, and C. Wilson, “Evaluation of pattern classifiers for fingerprint and OCR applications,” Patt. Recog. 27, 485–501 (1994).

[CrossRef]

R. Gonzalez and R. Woods, Digital Image Processing (Addison-Wesley, New York, 1993).

I. Cox, J. Ghosn, and P. Yianilos, “Feature-based face recognition using mixture–distance,” in Computer Vision and Pattern Recognition (IEEE Press, Piscataway, N.J., 1996).

K. Fukunaga and J. Young, “Pattern recognition and neural engineering,” in Neural Networks, Concepts, Applications and Implementations, P. Antognetti and V. Milutinovic, eds. (Prentice Hall, EngleWood Cliffs, N.J., 1991), Vol. 1, pp. 10–33.

H. Lodish, D. Baltimore, A. Berk, S. Zipursky, P. Matsudaira, and J. Darnell, Molecular Cell Biology (Scientific American, New York, 1995).

L. Mango, “Deducing false negatives in clinical practice: the role of neural network technology,” Am. J. Obstetr. Gynecol. 175, 1114–1119 (1996).

[CrossRef]

M. Astion and P. Wilding, “The application of backpropagation neural networks to problems in pathology,” Arch. Pathol. Lab. Med. 116, 995–1001 (1992).

[PubMed]

M. Soriano and C. Saloma, “Cell classification by a learning principal components analyzer and a backpropagation neural network,” Bioimaging 3, 168–175 (1995).

[CrossRef]

C. An, L. Petrovic, and A. Marchevsky, “The application of image analysis and neural network technology to the study of large cell liver cells,” Hepatocell Carcin. 26, 1224–2230 (1997).

D. Burton, “Text-dependent speaker verification using vector quantization source coding,” IEEE Trans. Acoust. Speech Signal Process. ASSP-35, 133–140 (1987).

[CrossRef]

S. Lawrence, C. Lee Giles, A. C. Tsoi, and A. Back, “Face recognition: a convolutional neural-network approach,” IEEE Trans. Neural Networks 8, 98–113 (1997).

[CrossRef]

A. Jain and J. Mao, “Guest editorial: special issue on artificial neural networks and statistical pattern recognition,” IEEE Trans. Neural Networks 8, 1–3 (1997).

[CrossRef]

F. Tsung and G. Cottrell, “Learning in recurrent finite difference networks,” Int. J. Neural Sys. 6, 249–255 (1995).

[CrossRef]

M. Brickley, J. Coupe, and J. Shepherd, “Performance of a computer-simulated neural network trained to categorize normal, premalignant and malignant oral smears,” J. Oral Pathol. Med. 25, 424–430 (1996).

[CrossRef]
[PubMed]

S. Shiotani, T. Fukuda, and F. Arai, “Cell recognition by image processing (recognition of dead or living plant cells by neural network),” JSME Int. J. Ser. C 371, 233–240 (1994).

T. Sanger, “Optimal unsupervised learning in a single-layer linear feed forward neural network,” Neural Networks 2, 459–473 (1989).

[CrossRef]

J. Blue, G. Candela, P. Grother, R. Chellapa, and C. Wilson, “Evaluation of pattern classifiers for fingerprint and OCR applications,” Patt. Recog. 27, 485–501 (1994).

[CrossRef]

Y. Qi and B. Hunt, “Signature verification using global and grid features,” Patt. Recog. 27, 1621–1629 (1994).

[CrossRef]

L. Gupta, R. Mohammed, and R. Tammana, “A neural network approach to robust shape classification,” Pattern Recog. 23, 563–568 (1990).

[CrossRef]

R. Chellapa, C. Wilson, and S. Sirohey, “Human and machine recognition of faces,” Proc. IEEE 83, 705–740 (1995).

[CrossRef]

T. Watkin and A. Rau, “The statistical mechanics of learning a rule,” Rev. Mod. Phys. 65, 499–556 (1994).

[CrossRef]

D. Beymer and T. Poggio, “Image representations for visual learning,” Science 272, 1905–1909 (1996).

[CrossRef]
[PubMed]

G. Cottrell and J. Metcalfe “EMPATH: face, emotion and gender recognition using holons,” in Vol. 3 of Advances in Neural Information Processing Systems Series (Morgan Kaufmann, San Mateo, Calif., 1991), pp. 564–571.

L. Bottou, C. Cortes, J. Denker, H. Drucker, I. Guyon, L. Jackel, Y. Le Cun, U. Muller, E. Sackinger, P. Simard, and V. Vapnik, “Comparison of classifier methods: a case study in handwritten digit recognition,” in Proceedings of the International Conference on Pattern Recognition (IEEE Comput. Soc. Press, Los Alamitos, Calif., 1994), Vol. 2, pp. 77–82.

H. Lodish, D. Baltimore, A. Berk, S. Zipursky, P. Matsudaira, and J. Darnell, Molecular Cell Biology (Scientific American, New York, 1995).

B. Alberts, D. Bray, J. Lewis, M. Raff, K. Roberts, and J. Watson, Molecular Biology of the Cell (Garland, New York, 1989).

R. Gonzalez and R. Woods, Digital Image Processing (Addison-Wesley, New York, 1993).

T. Masters, Signal and Image Processing With Neural Networks (Wiley, New York, 1993).

S. Haykin, Neural Network—A Comprehensive Foundation (Macmillan, New York, 1994).

M. McCord Nelson, and W. Illington, A Practical Guide to Neural Nets (Addison-Wesley, Reading, Mass., 1991).

C. Bishop, Neural Networks for Statistical Pattern Recognition (Oxford U. Press, Oxford, 1994).

I. Cox, J. Ghosn, and P. Yianilos, “Feature-based face recognition using mixture–distance,” in Computer Vision and Pattern Recognition (IEEE Press, Piscataway, N.J., 1996).

D. Rosenthal and L. Mango, “Applications of neural networks for interactive diagnosis of anatomic pathology specimens,” in Compendium on the Computerized Cytology and Histology Laboratory, Tutorials of Cytology, G. Weid, P. Bartels, D. Rosenthal, and U. Schenck, eds. (Karger, Chicago, 1994), pp. 173–184.

K. Fukunaga, Introduction to Statistical Pattern Recognition, 2nd ed. (Macmillan, New York, 1990).

K. Fukunaga and J. Young, “Pattern recognition and neural engineering,” in Neural Networks, Concepts, Applications and Implementations, P. Antognetti and V. Milutinovic, eds. (Prentice Hall, EngleWood Cliffs, N.J., 1991), Vol. 1, pp. 10–33.

A. Dawson, R. Austin, and D. Weinberg, “Nuclear grading of breast carcinoma by image analysis: classification by multivariate and neural network analysis,” Am. J. Clin. Pathol. (Suppl. 4) 95, 529–530.

J. Tou and R. Gonzalez, Pattern Recognition Principles (Addison-Wesley, London, 1974).

A. Papoulis, Probability, Random Variables, and Stochastic Processes, 2nd ed. (McGraw-Hill, New York, 1984).

G. Parry, “Speckle patterns in partially coherent light,” in Laser Speckle and Related Phenomena, Vol. 9 of Topics in Applied Physics Series (Springer-Verlag, Berlin, 1984).

J. Chamberlain, The Principles of Interferometric Spectroscopy (Wiley, New York, 1979), Chap. 9.

V. Daria, O. Nakamura, C. Palmes-Saloma, K. Fujita, C. Saloma, H. Kondoh, and S. Kawata, “Long-depth imaging of turbid biological samples by two-photon fluorescence microscopy,” paper presented at the Nineteenth Meeting of the Japan Society for Laser Microscopy, Nagoya, Japan, 8–10 May 1997.

S. Inoue, Video Microscopy (Plenum, New York, 1986).

J. Proakis and D. Manolakis, Digital Signal Processing—Principles, Algorithm, and Applications, 2nd ed. (Macmillan, New York, 1992), pp. 41–43.

L. Levi, Applied Optics—A Guide to Optical System Design (Wiley, New York, 1968), Vol. 1, pp. 152–154.

W. Press, S. Teukolsky, W. Vetterling, and B. Flannery, Numerical Recipes in C—The Art of Scientific Computing, 2nd ed. (Cambridge U. Press, New York, 1992).