Biomedical Engineering Reference
In-Depth Information
References
1.
Powner, E.T., Yalcinkaya, F. (1997). Intelligent biosensors.
Sensor Review
. 17(2): 107-116.
2.
Collings, A.F., Caruso, F. (1997). Biosensors: recent advances.
Rep. Prog. Phys.
60: 1397-1445.
3.
Griffiths, D., Hall, G. (1993). Biosensors—what real progress is being made?
Trends Biotechnol.
11(4): 122-130.
4.
Gaura, E., Newman, R.M. (2004). Smart, intelligent and cogent MEMS based sensors. In:
Proceedings of the 2004 IEEE International Symposium on Intelligent Control
. Taipei, Taiwan,
431-436.
5.
Rankey, P.G. (2002). Smart sensors.
Sensor Review.
22(4): 312-318.
6.
Powner, E.T., Yalcinkaya, F. (1995). From basic sensors to intelligent sensors: definitions and
examples.
Sensor Review
. 15(4): 19-22.
7.
Yamasaki, H. (1996). What are the intelligent sensors. In:
Intelligent Sensors
, Yamasaki, H., ed.,
Amsterdam: Elsevier, pp. 1-17.
8.
Duda, R.O., Hart, P.E., Stork, D.G. (2000).
Pattern Classification
. Second Edition. New York:
John Wiley.
9.
Ciaccio, E.J., Dunn, S.M., Akay, M. (1993). Biosignal pattern recognition and interpretation
systems. Part 1 of 4: fundamental concepts.
IEEE Eng. Med. Biol.
12(3): 89-97.
10.
Ciaccio, E.J., Dunn, S.M., Akay, M. (1993). Biosignal pattern recognition and interpretation sys-
tems. Part 2 of 4: methods for feature extraction and selection.
IEEE Eng. Med. Biol.
12(4): 106-113.
11.
Ciaccio, E.J., Dunn, S.M., Akay, M. (1993). Biosignal pattern recognition and interpretation
systems. Part 3 of 4: Methods of classification.
IEEE Eng. Med. Biol.
12(3): 89-97.
12.
Haykin, S. (1994).
Neural Networks: A Comprehensive Foundation
. New York: Macmillan.
13.
Fausett, L. (1994).
Fundamentals of Neural Networks
. Englewood Cliffs, N.J.: Prentice Hall.
14.
Hush, D.R., Horne, B.G. (1993). Progress in supervised neural networks.
IEEE Signal Process.
Magazine
. 10(1): 8-39.
15.
Kohonen, T. (1997).
Self-Organizing Maps
. New York: Springer.
16.
Gupta, M.M., Knopf, G.K. (1994).
Neuro-Vision Systems: Principles and Applications
. New York:
IEEE Press.
17.
Zupan, J., Novic, M., Ruisanchez, I. (1997). Kohonen and counter propagation artificial neu-
ral networks in analytical chemistry.
Chemometr. Intell. Lab. Syst
. 38: 1-23.
18.
Taib, M.N., Narayanaswamy, R. (1997). Multichannel calibration technique for optical-fibre
chemical sensor using artificial neural network.
Sensors Actuators
38-39: 365-370.
19.
Suah, F.B.M., Ahmad, M., Taib, M.N. (2003). Applications of artificial neural network on sig-
nal processing of optical fibre pH sensor based on bromophenol blue doped with sol-gel film.
Sensors Actuators
90: 182-188.
20.
Suah, F.B.M., Ahmad, M., Taib, M.N. (2003). Optimisation of the range of an optical fibre pH
sensor using a feed-forward artificial neural network.
Sensors Actuators
90: 175-181.
21.
Raimundo, I.M., Narayanaswamy, R. (2001). Simultaneous determination of relative humid-
ity and ammonia in air employing an optical fibre sensor and neural network.
Sensors
Actuators
74: 60-68.
22.
Ferreira, L.S., De Souza, M.B., Folly, R.O.M. (2001). Development of an alcohol fermentation
control system based on biosensor measurements interpreted by neural networks.
Sensors
Actuators
75: 166-171.
23.
Zupan, J., Novic, M., Gasteiger, J. (1995). Neural networks with counter-propagation learning
strategy used for modelling.
Chrometr. Intell. Lab. Syst.
27: 175-187.
24.
Lyons, W.B., Flanagan, C., Lochmann, S., Ewald, H., Lewis, E. (2001). A multipoint optical
evanescent wave U-bend sensor system based on artificial neural network pattern recogni-
tion. In:
Advanced Photonic Sensors and Applications II,
Asundi, A. K., Osten, W., Varadan, V.K.,
eds., Proceedings of SPIE Vol. 4596: 320-328.
25.
Blank, T.B, Brown, S.D. (1993). Nonlinear multivariate mapping of chemical data using feed-
forward neural networks.
Anal. Chem
. 65: 3081-3089.
26.
Bachmann, T.T., Leca, B., Vilatte, F., Marty, J.-L., Fournier, D., Schmid, R.D. (2000). Improved
multianalyte detection of organophosphates and carbamates with disposable multielectrode
