-
1
-
-
0035329583
-
Selecting inputs for modelling using normalized higher order statistics and independent component analysis
-
May
-
A. D. Back and T. P. Trappenberg, "Selecting inputs for modelling using normalized higher order statistics and independent component analysis," IEEE Trans. Neural Netw., vol. 12, no. 3, pp. 612-617, May 2001.
-
(2001)
IEEE Trans. Neural Netw
, vol.12
, Issue.3
, pp. 612-617
-
-
Back, A.D.1
Trappenberg, T.P.2
-
2
-
-
0031381525
-
Wrappers for feature subset selection
-
R. Kohavi and G. John, "Wrappers for feature subset selection," Artif. Intell., vol. 97, no. 1-2, pp. 273-324, 1997.
-
(1997)
Artif. Intell
, vol.97
, Issue.1-2
, pp. 273-324
-
-
Kohavi, R.1
John, G.2
-
3
-
-
33745561205
-
An introduction to variable feature selection
-
I. Guyon and A. Elisseeff, "An introduction to variable feature selection," J. Mach. Learn. Res., vol. 3, pp. 1157-1182, 2003.
-
(2003)
J. Mach. Learn. Res
, vol.3
, pp. 1157-1182
-
-
Guyon, I.1
Elisseeff, A.2
-
4
-
-
13844298045
-
Estimating optimal feature subsets using efficient estimation of high-dimensional mutual information
-
Jan
-
T. W. S. Chow and D. Huang, "Estimating optimal feature subsets using efficient estimation of high-dimensional mutual information," IEEE Trans. Neural Netw., vol. 16, no. 1, pp. 213-224, Jan. 2005.
-
(2005)
IEEE Trans. Neural Netw
, vol.16
, Issue.1
, pp. 213-224
-
-
Chow, T.W.S.1
Huang, D.2
-
5
-
-
3843072084
-
Feature selection in MLPs and SVMs based on maximum output information
-
Jul
-
V. Sindhwani, S. Rakshit, D. Deodhare, D. Erdogmus, J. Principe, and P. Niyogi, "Feature selection in MLPs and SVMs based on maximum output information," IEEE Trans. Neural Netw., vol. 15, no. 4, pp. 937-948, Jul. 2004.
-
(2004)
IEEE Trans. Neural Netw
, vol.15
, Issue.4
, pp. 937-948
-
-
Sindhwani, V.1
Rakshit, S.2
Deodhare, D.3
Erdogmus, D.4
Principe, J.5
Niyogi, P.6
-
6
-
-
0348139702
-
Dimension reduction by local principal component analysis
-
N. Kambhatla and T. K. Leen, "Dimension reduction by local principal component analysis," Neural Comput., vol. 9, no. 7, pp. 1493-1516, 1997.
-
(1997)
Neural Comput
, vol.9
, Issue.7
, pp. 1493-1516
-
-
Kambhatla, N.1
Leen, T.K.2
-
7
-
-
9244258603
-
The pre-image problem in kernel methods
-
Nov
-
J. T. Kwok and I. W. Tsang, "The pre-image problem in kernel methods," IEEE Trans. Neural Netw., vol. 15, no. 6, pp. 1517-1525, Nov. 2004.
-
(2004)
IEEE Trans. Neural Netw
, vol.15
, Issue.6
, pp. 1517-1525
-
-
Kwok, J.T.1
Tsang, I.W.2
-
8
-
-
1242331294
-
A nonnegative PCA algorithm for independent component analysis
-
Jan
-
M. D. Plumbley and E. Oja, "A nonnegative PCA algorithm for independent component analysis," IEEE Trans. Neural Netw., vol. 15, no. 1, pp. 66-76, Jan. 2004.
-
(2004)
IEEE Trans. Neural Netw
, vol.15
, Issue.1
, pp. 66-76
-
-
Plumbley, M.D.1
Oja, E.2
-
9
-
-
0036740201
-
Fast orthogonal forward selection algorithm for feature subset selection
-
Sep
-
K. Z. Mao, "Fast orthogonal forward selection algorithm for feature subset selection," IEEE Trans. Neural Netw., vol. 13, no. 5, pp. 1218-1224, Sep. 2002.
-
(2002)
IEEE Trans. Neural Netw
, vol.13
, Issue.5
, pp. 1218-1224
-
-
Mao, K.Z.1
-
10
-
-
0742307292
-
Orthogonal forward selection and backward elimination algorithms for feature subset selection
-
Feb
-
K. Z. Mao, "Orthogonal forward selection and backward elimination algorithms for feature subset selection," IEEE Trans. Syst., Man, Cybern. B, Cybern., vol. 34, no. 1, pp. 629-634, Feb. 2004.
-
(2004)
IEEE Trans. Syst., Man, Cybern. B, Cybern
, vol.34
, Issue.1
, pp. 629-634
-
-
Mao, K.Z.1
-
11
-
-
2942734703
-
Benefitting from the variables that variable selection discards
-
R. Caruana and V. De Sa, "Benefitting from the variables that variable selection discards," J. Mach. Learn. Res., vol. 3, pp. 1245-1264, 2003.
-
(2003)
J. Mach. Learn. Res
, vol.3
, pp. 1245-1264
-
-
Caruana, R.1
De Sa, V.2
-
12
-
-
0032674833
-
A formal selection and pruning algorithm for feedforward artificial network optimization
-
Jul
-
Ponnapalli, "A formal selection and pruning algorithm for feedforward artificial network optimization," IEEE Trans. Neural Netw., vol. 10, no. 4, pp. 964-968, Jul. 1999.
-
(1999)
IEEE Trans. Neural Netw
, vol.10
, Issue.4
, pp. 964-968
-
-
Ponnapalli1
-
13
-
-
0001352974
-
Pruning from adaptive regularization
-
L. K. Kansen and C. E. Rasmussen, "Pruning from adaptive regularization," Neural Comput., vol. 6, no. 6, pp. 1223-1232, 1994.
-
(1994)
Neural Comput
, vol.6
, Issue.6
, pp. 1223-1232
-
-
Kansen, L.K.1
Rasmussen, C.E.2
-
14
-
-
0027662338
-
Pruning algorithms - A survey
-
Sep
-
R. Reed, "Pruning algorithms - A survey," IEEE Trans. Neural Netw., vol. 4, no. 5, pp. 740-747, Sep. 1993.
-
(1993)
IEEE Trans. Neural Netw
, vol.4
, Issue.5
, pp. 740-747
-
-
Reed, R.1
-
15
-
-
0000155950
-
The cascade correlation learning architecture
-
San Mateo, CA: Morgan Kaufmann
-
S. E. Fahlman and C. Iebiére, "The cascade correlation learning architecture," in Advances in Neural Information Processing Systems2, 1993, pp. 524-532, San Mateo, CA: Morgan Kaufmann.
-
(1993)
Advances in Neural Information Processing Systems2
, pp. 524-532
-
-
Fahlman, S.E.1
Iebiére, C.2
-
16
-
-
0031146959
-
Constructive algorithms for structure learning in feedforward neural networks for regression problems
-
May
-
T. Y. Kwok and D. Y. Yeung, "Constructive algorithms for structure learning in feedforward neural networks for regression problems," IEEE Trans. Neural Netw., vol. 8, no. 3, pp. 630-645, May 1997.
-
(1997)
IEEE Trans. Neural Netw
, vol.8
, Issue.3
, pp. 630-645
-
-
Kwok, T.Y.1
Yeung, D.Y.2
-
17
-
-
0042525842
-
Neural-network construction and selection in nonlinear modeling
-
Jul
-
I. Rivals and L. Personnaz, "Neural-network construction and selection in nonlinear modeling," IEEE Trans. Neural Netw., vol. 14, no. 4, pp. 804-819, Jul. 2003.
-
(2003)
IEEE Trans. Neural Netw
, vol.14
, Issue.4
, pp. 804-819
-
-
Rivals, I.1
Personnaz, L.2
-
18
-
-
13844256702
-
A generalized growing and pruning RBF (GGAP-RBF) neural network for function approximation
-
Jan
-
G. B. Huang, P. Saratchandran, and N. Sundararajan, "A generalized growing and pruning RBF (GGAP-RBF) neural network for function approximation," IEEE Trans. Neural Netw., vol. 16, no. 1, pp. 57-67, Jan. 2005.
-
(2005)
IEEE Trans. Neural Netw
, vol.16
, Issue.1
, pp. 57-67
-
-
Huang, G.B.1
Saratchandran, P.2
Sundararajan, N.3
-
19
-
-
0038495007
-
Optimal pruning of feed-forward neural networks based upon the Schmidt procedure
-
F. J. Maldonado and M. T. Manry, "Optimal pruning of feed-forward neural networks based upon the Schmidt procedure," in 36th Asilomar Conf. Signals, Systems Computers, 2002, pp. 1024-1028.
-
(2002)
36th Asilomar Conf. Signals, Systems Computers
, pp. 1024-1028
-
-
Maldonado, F.J.1
Manry, M.T.2
-
20
-
-
0030608136
-
Variable selection with neural networks
-
T. Cibas, F. F.Soulié, P. Gallinanri, and S. Raudys, "Variable selection with neural networks," Neurocomput., vol. 12, pp. 223-248, 1996.
-
(1996)
Neurocomput
, vol.12
, pp. 223-248
-
-
Cibas, T.1
Soulié, F.F.2
Gallinanri, P.3
Raudys, S.4
-
21
-
-
0027577112
-
Bayesian selection of important features for feedforward neural networks
-
3, pp
-
K. L. Priddy, S. K. Rogers, D. W. Ruch, G. L. Tarr, and M. Kabrisky, "Bayesian selection of important features for feedforward neural networks," Neurocomput., vol. 5, no. 2, 3, pp. 91-103, 1993.
-
(1993)
Neurocomput
, vol.5
, Issue.2
, pp. 91-103
-
-
Priddy, K.L.1
Rogers, S.K.2
Ruch, D.W.3
Tarr, G.L.4
Kabrisky, M.5
-
22
-
-
0013125561
-
Feature selection with neural networks
-
Jan
-
P. Leray and P. Gallinari, "Feature selection with neural networks," Behaviormetrika, vol. 26, Jan. 1999.
-
(1999)
Behaviormetrika
, vol.26
-
-
Leray, P.1
Gallinari, P.2
-
23
-
-
0030188379
-
Neural network studies. 2. variable selection
-
I. V. Tetko, A. E. P. Villa, and D. J. Livingstone, "Neural network studies. 2. variable selection," J. Chem. Inf. Comput. Sci., vol. 36, no. 4, pp. 794-803, 1996.
-
(1996)
J. Chem. Inf. Comput. Sci
, vol.36
, Issue.4
, pp. 794-803
-
-
Tetko, I.V.1
Villa, A.E.P.2
Livingstone, D.J.3
-
24
-
-
0028547556
-
Floating search methods in feature selection
-
P. Pudil, J. Novovičová, and J. Kittler, "Floating search methods in feature selection," Pattern Recognit. Lett., vol. 15, pp. 1119-1125, 1994.
-
(1994)
Pattern Recognit. Lett
, vol.15
, pp. 1119-1125
-
-
Pudil, P.1
Novovičová, J.2
Kittler, J.3
-
25
-
-
0017535866
-
A branch and bound algorithm for feature subset selection
-
Sep
-
P. M. Narendra and K. Fukunaga, "A branch and bound algorithm for feature subset selection," IEEE Trans. Comput., vol. C-26, no. 9, pp. 917-922, Sep. 1977.
-
(1977)
IEEE Trans. Comput
, vol.C-26
, Issue.9
, pp. 917-922
-
-
Narendra, P.M.1
Fukunaga, K.2
-
26
-
-
0002526012
-
On selecting features for pattern classifiers
-
S. D. Stearns, "On selecting features for pattern classifiers," 3rd Int. Conf. Pattern Recognition, pp. 71-75, 1976.
-
(1976)
3rd Int. Conf. Pattern Recognition
, pp. 71-75
-
-
Stearns, S.D.1
-
27
-
-
0346825283
-
Mlps (mono-layer polynomials and multi-layer perceptrons) for nonlinear modeling
-
I. Rivals and L. Personnaz, "Mlps (mono-layer polynomials and multi-layer perceptrons) for nonlinear modeling," J. Mach. Learn. Res., vol. 3, pp. 1383-1398, 2003.
-
(2003)
J. Mach. Learn. Res
, vol.3
, pp. 1383-1398
-
-
Rivals, I.1
Personnaz, L.2
-
28
-
-
2942701493
-
Ranking a random feature for variable and feature selection
-
H. Stoppiglia, G. Dreyfus, R. Dubois, and Y. Oussar, "Ranking a random feature for variable and feature selection," J. Mach. Learn. Res., vol. 3, pp. 1399-1414, 2003.
-
(2003)
J. Mach. Learn. Res
, vol.3
, pp. 1399-1414
-
-
Stoppiglia, H.1
Dreyfus, G.2
Dubois, R.3
Oussar, Y.4
-
29
-
-
0038548172
-
Sparse kernel regression modelling using combined locally regularised orthogonal least squares and D-Optimality experimental design
-
Jun
-
S. Chen, X. Hong, and C. J. Harris, "Sparse kernel regression modelling using combined locally regularised orthogonal least squares and D-Optimality experimental design," IEEE Trans. Autom. Control, vol. 48, no. 6, pp. 1029-1026, Jun. 2003.
-
(2003)
IEEE Trans. Autom. Control
, vol.48
, Issue.6
, pp. 1029-1026
-
-
Chen, S.1
Hong, X.2
Harris, C.J.3
-
30
-
-
1842430977
-
Sparse modelling using orthogonal forward regression with PRESS statistic and regularization
-
Apr
-
S. Chen, X. Hong, C. J. Harris, and P. M. Sharkey, "Sparse modelling using orthogonal forward regression with PRESS statistic and regularization," IEEE Trans. Syst., Man, Cybern. B, Cybern., vol. 34, no. 2, pp. 898-911, Apr. 2004.
-
(2004)
IEEE Trans. Syst., Man, Cybern. B, Cybern
, vol.34
, Issue.2
, pp. 898-911
-
-
Chen, S.1
Hong, X.2
Harris, C.J.3
Sharkey, P.M.4
-
31
-
-
0035245192
-
Variable selection algorithm for the construction of MIMO operating point dependent neurofuzzy networks
-
Feb
-
X. Hong and C. J. Harris, "Variable selection algorithm for the construction of MIMO operating point dependent neurofuzzy networks," IEEE Trans. Fuzzy Syst., vol. 9, no. 1, pp. 88-101, Feb. 2001.
-
(2001)
IEEE Trans. Fuzzy Syst
, vol.9
, Issue.1
, pp. 88-101
-
-
Hong, X.1
Harris, C.J.2
-
32
-
-
0024771664
-
Orthogonal least squares methods and their application to non-linear system identification
-
S. Chen, S. A. Billings, and W. Luo, "Orthogonal least squares methods and their application to non-linear system identification," Int. J. Control, vol. 50, no. 5, pp. 1873-1896, 1989.
-
(1989)
Int. J. Control
, vol.50
, Issue.5
, pp. 1873-1896
-
-
Chen, S.1
Billings, S.A.2
Luo, W.3
-
33
-
-
0026116468
-
Orthogonal least squares learning algorithm for radial basis function networks
-
Mar
-
S. Chen, C. F. N. Cowan, and P. M. Grant, "Orthogonal least squares learning algorithm for radial basis function networks," IEEE Trans. Neural Netw., vol. 2, no. 2, pp. 302-309, Mar. 1991.
-
(1991)
IEEE Trans. Neural Netw
, vol.2
, Issue.2
, pp. 302-309
-
-
Chen, S.1
Cowan, C.F.N.2
Grant, P.M.3
-
34
-
-
84949203556
-
Locally regularised orthogonal least squares algorithm for the construction of sparse kernel regression models
-
S. Chen, "Locally regularised orthogonal least squares algorithm for the construction of sparse kernel regression models," in Proc. 6th Int. Conf. Signal Processing, 2002, vol. 2, pp. 1229-1232.
-
(2002)
Proc. 6th Int. Conf. Signal Processing
, vol.2
, pp. 1229-1232
-
-
Chen, S.1
-
35
-
-
0023381883
-
Piecewise linear identification of nonlinear systems
-
S. A. Billings and W. S. F. Voon, "Piecewise linear identification of nonlinear systems," Int. J. Control, vol. 46, pp. 215-235, 1987.
-
(1987)
Int. J. Control
, vol.46
, pp. 215-235
-
-
Billings, S.A.1
Voon, W.S.F.2
-
36
-
-
0008577261
-
-
Belmont, CA: Wadsworth
-
L. Breiman, J. H. Friedman, R. A. Olshen, and C. J. Stone, Classification and Regression Tress. Belmont, CA: Wadsworth, 1984.
-
(1984)
Classification and Regression Tress
-
-
Breiman, L.1
Friedman, J.H.2
Olshen, R.A.3
Stone, C.J.4
-
37
-
-
0002432565
-
Multivariate adaptive regression splines
-
J. H. Friedman, "Multivariate adaptive regression splines," Ann. Statistics, vol. 19, no. 1, pp. 1-141, 1991.
-
(1991)
Ann. Statistics
, vol.19
, Issue.1
, pp. 1-141
-
-
Friedman, J.H.1
-
38
-
-
0016556021
-
A new approach to manipulator control: The cerebellar model articulation controller (CMAC)
-
J. S. Albus, "A new approach to manipulator control: The cerebellar model articulation controller (CMAC)," J. Dynam. Syst., Meas. Control - Trans. ASME, vol. 97, no. 3, pp. 220-227, 1975.
-
(1975)
J. Dynam. Syst., Meas. Control - Trans. ASME
, vol.97
, Issue.3
, pp. 220-227
-
-
Albus, J.S.1
-
39
-
-
0016555419
-
Data storage in the cerebellar model articulation controller (CMAC)
-
J. S. Albus, "Data storage in the cerebellar model articulation controller (CMAC)," J. Dynam. Syst., Meas. Control - Trans. ASME, vol. 97, no. 3, pp. 228-233, 1975.
-
(1975)
J. Dynam. Syst., Meas. Control - Trans. ASME
, vol.97
, Issue.3
, pp. 228-233
-
-
Albus, J.S.1
-
40
-
-
0010112552
-
A Local Approach for Sizing the Multilayer Perceptron,
-
Ph.D. dissertation, Dept. Elect. Eng, Univ. Texas, Arlington
-
K. K. Kim, "A Local Approach for Sizing the Multilayer Perceptron," Ph.D. dissertation, Dept. Elect. Eng., Univ. Texas, Arlington, 1996.
-
(1996)
-
-
Kim, K.K.1
-
41
-
-
0030653579
-
Modular neural network architecture using piecewise linear mapping
-
S. Subbarayan, K. Kim, M. T. Manry, V. Devarajan, and H. Chen, "Modular neural network architecture using piecewise linear mapping," 30th Asilomar Conf. Signals, Systems Computers, vol. 2, pp. 1171-1175, 1996.
-
(1996)
30th Asilomar Conf. Signals, Systems Computers
, vol.2
, pp. 1171-1175
-
-
Subbarayan, S.1
Kim, K.2
Manry, M.T.3
Devarajan, V.4
Chen, H.5
-
42
-
-
0001025418
-
Bayesian interpolation
-
D. J. C. MacKay, "Bayesian interpolation," Neural Comput., vol. 4, no. 3, pp. 415-447, 1992.
-
(1992)
Neural Comput
, vol.4
, Issue.3
, pp. 415-447
-
-
MacKay, D.J.C.1
-
43
-
-
0029368179
-
Network-growth approach to design of feed-forward neural networks
-
F. L. Chung and T. Lee, "Network-growth approach to design of feed-forward neural networks," IEE Proc. Control Theory Applications, vol. 142, no. 5, pp. 486-492, 1995.
-
(1995)
IEE Proc. Control Theory Applications
, vol.142
, Issue.5
, pp. 486-492
-
-
Chung, F.L.1
Lee, T.2
-
44
-
-
0025964567
-
Back-propagation algorithm that varies the number of hidden units
-
Y. Hirose, K. Yamashita, and S. Hijiya, "Back-propagation algorithm that varies the number of hidden units," Neural Netw., vol. 4, pp. 61-66, 1991.
-
(1991)
Neural Netw
, vol.4
, pp. 61-66
-
-
Hirose, Y.1
Yamashita, K.2
Hijiya, S.3
-
46
-
-
0028544395
-
Network information criterion-determining the number of hidden units for an artificial neural network model
-
Nov
-
N. Murata, S. Yoshizawa, and S. Amari, "Network information criterion-determining the number of hidden units for an artificial neural network model," IEEE Trans. Neural Netw., vol. 5, no. 6, pp. 865-872, Nov. 1994.
-
(1994)
IEEE Trans. Neural Netw
, vol.5
, Issue.6
, pp. 865-872
-
-
Murata, N.1
Yoshizawa, S.2
Amari, S.3
-
49
-
-
0033636139
-
Support vector machine classification an validation of cancer tissue samples using microarray expression data
-
T. Furey, N. C. Duffy, N. Bednarski, D. M. Schummer, and D. Haussler, "Support vector machine classification an validation of cancer tissue samples using microarray expression data," Bioinformatics, vol. 16, pp. 906-914, 2000.
-
(2000)
Bioinformatics
, vol.16
, pp. 906-914
-
-
Furey, T.1
Duffy, N.C.2
Bednarski, N.3
Schummer, D.M.4
Haussler, D.5
-
50
-
-
0029941179
-
Spatial pattern analysis of functional brain images using partial least squares
-
A. R. McIntosh, F. L. Bookstein, J. V. Haxby, and C. L. Grady, "Spatial pattern analysis of functional brain images using partial least squares," Neuroimage, vol. 3, pp. 143-157, 1996.
-
(1996)
Neuroimage
, vol.3
, pp. 143-157
-
-
McIntosh, A.R.1
Bookstein, F.L.2
Haxby, J.V.3
Grady, C.L.4
-
51
-
-
0001098205
-
chapter Estimation of Principal Components and Related Models by Iterative Least Squares
-
New York: Academic Press
-
H. Wold, "chapter Estimation of Principal Components and Related Models by Iterative Least Squares," in Multivariate Analysis. New York: Academic Press, 1966, pp. 391-420.
-
(1966)
Multivariate Analysis
, pp. 391-420
-
-
Wold, H.1
-
52
-
-
84871900799
-
A Comprehensive Foundation
-
2 ed. Englewood Cliffs, N.J, Prentice-Hall
-
S. Haykin, "A Comprehensive Foundation," in Neural Networks, 2 ed. Englewood Cliffs, N.J.: Prentice-Hall, 1999.
-
(1999)
Neural Networks
-
-
Haykin, S.1
-
53
-
-
0027262895
-
Multilayer feedforward networks with a nonpolynomial activation function can approximate any function
-
M. Leshno, V. Lin, and S. Schocken, "Multilayer feedforward networks with a nonpolynomial activation function can approximate any function," Neural Netw., vol. 6, no. 6, pp. 861-867, 1993.
-
(1993)
Neural Netw
, vol.6
, Issue.6
, pp. 861-867
-
-
Leshno, M.1
Lin, V.2
Schocken, S.3
-
54
-
-
0033316848
-
Sizing of the multilayer perceptron via modular networks
-
Madison, WI, Aug
-
H. Chandrasekaran, K. K. Kim, and M. T. Manry, "Sizing of the multilayer perceptron via modular networks," in Proc. Neural Networks for Signal Processing IX (NNSP'99), Madison, WI, Aug. 1999, pp. 215-224.
-
(1999)
Proc. Neural Networks for Signal Processing IX (NNSP'99)
, pp. 215-224
-
-
Chandrasekaran, H.1
Kim, K.K.2
Manry, M.T.3
-
55
-
-
0027851253
-
Constructive proof of efficient pattern storage in the multilayer perceptron
-
A. Gopalakrishnan, M. S. Chen, X. Jiang, and M. T. Manry, "Constructive proof of efficient pattern storage in the multilayer perceptron," in 27th Asilomar Conf. Signals, System, Systems, Computers, 1993, vol. 1, pp. 386-390.
-
(1993)
27th Asilomar Conf. Signals, System, Systems, Computers
, vol.1
, pp. 386-390
-
-
Gopalakrishnan, A.1
Chen, M.S.2
Jiang, X.3
Manry, M.T.4
-
56
-
-
1542365112
-
Dimensionality reduction via sparse support vector machines
-
Mar
-
J. Bi, K. P. Bennett, M. Embrechts, C. M. Breneman, and M. Song, "Dimensionality reduction via sparse support vector machines," J. Mach. Learn. Res., vol. 3, pp. 1229-1243, Mar. 2003.
-
(2003)
J. Mach. Learn. Res
, vol.3
, pp. 1229-1243
-
-
Bi, J.1
Bennett, K.P.2
Embrechts, M.3
Breneman, C.M.4
Song, M.5
-
57
-
-
0027382740
-
Surface parameter retrieval using fast learning neural networks
-
M. S. Dawson, A. K. Fung, and M. T. Manry, "Surface parameter retrieval using fast learning neural networks," Remote Sens. Rev., vol. 7, no. 1, pp. 1-18, 1993.
-
(1993)
Remote Sens. Rev
, vol.7
, Issue.1
, pp. 1-18
-
-
Dawson, M.S.1
Fung, A.K.2
Manry, M.T.3
|