References
The following list of references is also available in BibTeX format .
Papers describing the basic ideas leading to this website
W . Maass,
T. Natschläger, and H. Markram.
Real-time computing without
stable states: A new framework for neural computation based on
perturbations .
Neural Computation , 14(11):2531-2560, 2002.
T . Natschläger, H. Markram, and W. Maass.
Computer models
and analysis tools for neural microcircuits .
In R. Kötter, editor, A Practical Guide to Neuroscience Databases and
Associated Tools , chapter 9. Kluver Academic Publishers (Boston),
2002.
W . Maass,
T. Natschläger, and H. Markram.
Computational models
for generic cortical microcircuits .
In J. Feng, editor, Computational Neuroscience: A Comprehensive
Approach . CRC-Press, 2002.
W . Maass,
T. Natschläger, and H. Markram.
A fresh look at real-time
computation in generic recurrent neural circuits .
submitted for publication , 2002.
W . Maass and
H. Markram.
Temporal integration in recurrent microcircuits .
In M. A. Arbib, editor, The Handbook of Brain Theory and Neural
Networks . MIT Press (Cambridge), 2nd edition, 2002.
T . Natschläger, W. Maass, and H. Markram.
The "liquid computer": A
novel strategy for real-time computing on time series .
Special Issue on Foundations of Information Processing of
TELEMATIK , 8(1):39-43, 2002.
H . Jaeger.
The
"echo state" approach to analysing and training recurrent neural
networks .
Technical Report GMD Report 148, German National Research Center for
Information Technology, 2001.
H . Haas H. Jaeger.
Harnessing nonlinearity: Predicting chaotic systems and saving energy in wireless
communication .
Science , pages 78-80, April 2 2004.
Theory
Applications to specific tasks
S . Häusler,
H. Markram, and W. Maass.
Perspectives
of the high dimensional dynamics of neural microcircuits from the point of
view of low dimensional readouts .
Complexity (special issue on Complex Adaptive Systems) , 2003.
(PDF )
R . A.
Legenstein, H. Markram, and W. Maass.
Input prediction and
autonomous movement analysis in recurrent circuits of spiking neurons .
Reviews in the Neurosciences (Special Issue on Neuroinformatics of Neural
and Artificial Computation) , 14(1-2):5-19, 2003.
W . Maass, R. A.
Legenstein, and H. Markram.
A new approach towards
vision suggested by biologically realistic neural microcircuit models .
In Proc. of the 2nd Workshop on Biologically Motivated Computer
Vision , Lecture Notes in Computer Science. Springer, Nov. 2002.
W . Maass,
T. Natschläger, and H. Markram.
A model for real-time
computation in generic neural microcircuits .
Proc. of NIPS 2002 , 15:229-236, 2002.
T . Natschläger and W. Maass.
Spiking neurons and the induction of finite state
machines .
Theoretical Computer Science: Special Issue on Natural Computing ,
287:251-265, 2002.
H . Jaeger.
Adaptive
nonlinear system identification with echo state networks .
Proc. NIPS 02, 2002.
D . Goldenholz.
Liquid computig: A real
effect .
Technical report, Boston University Department of Biomedical Engineering,
2002.
Books
