Biomedical Engineering Reference
In-Depth Information
biosensors using recombinant mutants of
Drosophila
acetylcholinesterase and artificial neural
networks.
Biosen. Bioelectr.
15: 193-201.
27.
Bowen, B.P., Scruggs, A., Enderlein, J., Sauer, M., Woodbury, N. (2004). Implementation of
neural networks for the identification of single molecules.
J. Phys. Chem.
108: 4799-4804.
28.
Lobanov, A.V., Borisov, I.A., Gordon, S.H., Greene, R.V., Leathers, T.D., Reshetilov, A.N.
(2001). Analysis of ethanol-glucose mixtures by two microbial sensors: application of chemo-
metrics and artificial neural networks for data processing.
Biosens. Bioelectr
. 16: 1001-1007.
29.
Bulsari, A., Saxen, H. (1994). Using feed-forward neural networks for estimation of microbial
concentration in a simulated biochemical process.
Biosens. Bioelectr
. 9: 105-109.
30.
Keller, P.E. (1999). Overview of electronic nose algorithms. In:
Proceedings of the International
Joint Conference on Neural Networks
. Vol. 1. pp. 309—312.
31.
Göpel, W., Ziegler, C., Breer, H., Schild, D., Apfelbach, R., Joerges, J., Malaka, R. (1998).
Bioelectronic noses: a status report Part I.
Biosens. Bioelectr.
13(3-4): 479-493.
32.
Ziegler, C., Göpel, W., Hammerle, H., Hatt, H., Jung, G., Laxhuber, L., Schmidt, H.-L., Schütz,
S., Vögtle, F., Zell, A. (1998). Bioelectronic noses: a status report. Part II.
Biosens. Bioelectr
. 13:
539-571.
33.
Kermani, B.G., Schiffman, S.S., Nagle, H.T. (1999). Using neural networks and genetic algo-
rithms to enhance performance in the electronic nose.
IEEE Trans. Biomed. Eng.
46(4): 429-439.
34.
Di Natale, C., Macagnano, A., Davide, F., D'Amico, A., Paolesse, R., Boschi, T., Faccio, M.,
Ferri, G. (1997). An electronic nose for food analysis.
Sensors Actuators
44: 521-526.
35.
Evans, P., Persaud, K.C., McNeish, A.S., Sneath, R.W., Hobson, N., Magan, N. (2000).
Evaluation of a radial basis function neural network for determination of wheat quality from
electronic nose data.
Sensors Actuators
69: 348-358.
36.
Llobet, E., Hines, E.L., Gardner, J.W., Franco, S. (1999). Non-destructive banana ripeness deter-
mination using a neural network-based electronic nose.
Measure. Sci. Technol.
10: 538-548.
37.
Brezmes, J., Llobet, E., Vilanova, X., Saiz, G., Correig, X. (2000). Fruit ripeness monitoring
using an electronic nose.
Sensors Actuators
69: 223-229.
38.
Dutta, R., Hines, E.L., Gardner, J.W., Udrea, D.D., Boilet, P. (2003). Non-destructive egg fresh-
ness determination: an electronic nose based approach.
Measure. Sci. Technol.
14: 190-198.
39.
Panigrahi, S., Balasubramanian, S., Gu, H., Logue, C., Marchello, M. (2006). Neural-network-
integrated electronic nose system for the identification of spoiled beef.
LWT.
39: 135-145.
40.
Brezmes, J., Ferreras, B., Llobet, E., Vilanova, X., Correig, X. (1997). Neural network based
electronic nose for classification of aromatic species.
Anal. Chim. Acta.
348: 503-509.
41.
Daqi, G., Shuyan, W., Yan, J. (2004). An electronic nose and modular radial basis function net-
work classifiers for recognizing multiple fragrant materials.
Sensors Actuators
97: 391-401.
42.
Pavlou, A.K., Magan, N., Jones, J.M., Brown, J., Klatser, P., Turner, A.P.F. (2004). Detection of
Mycobacterium tuberculosis
(TB) in vitro and in situ using electronic nose in combination with
a neural network system.
Biosens. Bioelectr
. 20: 538-544.
43.
Dutta, R., Morgan, D., Baker, N., Gardner, J.W., Hines, E.L. (2005). Identification of
Staphylococcus aureus
infections in hospital environment: electronic nose based approach.
Sensors Actuators
109: 355-362.
44.
Golden, J.P., Anderson, G.P., Cao, L.K., Ligler, F.S. (1994). Calibration methods for an evanes-
cent wave fiber optic sensor. In:
Annual International Conference of the IEEE Engineering in
Medicine and Biology—Proceedings
. Vol. 16(2). pp. 822-823.
45.
Wang W.W., Knopf G.K., Bassi A. (2005). Photoelectric properties of a detector based on dried
bacteriorhodopsin film.
Biosens. Bioelectr
. 21: 1309-1319.
46.
Wang, W.W., Knopf, G.K., Bassi, A. (2005). Protein-based photocell for high-speed motion
detection. In:
2005 IEEE International Conference on Control Applications.
pp. 731-736.
47.
Wang, W.W., Knopf, G.K., Bassi, A. (2005). Implementation of bidirectional motion detection
using protein based photoreceptors. In:
IEEE/ASME Advance Intelligent Mechatronics (AIM
2005)
. pp. 72-75.
48.
Knopf, G.K., Sangole, A. (2004). Interpolating scattered data using 2-D self-organizing feature
maps.
J. Graph. Models
66: 50-69.
49.
Blake, C.L., Merz, C.J. (1998).
UCI Repository of Machine Learning
, University of California,
Department of Information and Computer Science, Irvine, CA. [http://www.ics.uci.edu/
~mlearn/MLRepository.html].