Chaotic spiking oscillators
From Scholarpedia
| Toshimichi Saito (2007), Scholarpedia, 2(9):1831. | revision #38960 [link to/cite this article] | |||||||||||||||||||
Curator: Dr. Toshimichi Saito, Hosei University, Tokyo, Japan
Chaotic Spiking Oscillators (CSOs) are continuous-time autonomous circuits including an integrate-and-fire (IAF) switch and have the following properties.
- 1. The IAF switch is the key element to generate chaos. The IAF is suitable for hardware implementation and chaotic dynamics can be confirmed experimentally.
- 2. In a class of piecewise linear CSOs, return map is described using exact piecewise solution and chaos generation is guaranteed mathematically.
- 3. The CSO can be a building block of pulse-coupled neural networks (PCNNs) that has rich synchronous phenomena. The PCNN has some potential applications including image processing.
Contents |
Integrate-and-Fire Switching in Circuits
Chaotic circuits do not imply just a realization method of existing mathematical models but important real physical systems to investigate interesting nonlinear phenomena (Matsumoto, Chua and Komuro 1985; Maggio G. M., Feo O. D., Kennedy M. P. 1999; Ekwakil A. S., Kennedy M. P. 2001 ).
A variety of nonlinear elements are used in existing chaotic circuits and the IAF switch is used in the CSO.
In Fig. 1,
is a linear sub-circuit and
is the IAF switch.
If the capacitor voltage
reaches a threshold voltage
,
is reset to the base voltage
, instantaneously.
If the sub-circuit
consists of resistors and dependent sources, it can be replaced with the Thevenin equivalent sub-circuit and the circuit can exhibit periodic waveforms as shown in Fig. 1 (b).
This periodic behavior is basic for an integrate-and-fire neuron model which can be a building block of PCNN (Mirollo and Strogatz 1990; Hopfield and Herz 1995).
Applications of PCNNs include image processing (Campbell, Wang and Jayaprakash 1999), associative memory (Izhikevich 1999) and Spike-based communication (M. Maggio, Rulkov and Reggiani 2001).
If the sub-circuit
includes one memory element (inductor or capacitor) as shown in Fig.1 (c), the circuit can become a CSO.
In this case the IAF switch causes vibrate-and-fire dynamics that relates deeply to resonant-and-fire neuron models (Izhikevich 2001).
A Simple Circuit
If
includes 1 or more memory elements,
can vibrate below the threshold and the IAF switch can cause chaotic behavior.
Fig. 2 shows a simple example of the CSO.
In the figure
is a linear negative resistor.
If the capacitor voltage
is below the threshold
, the switch
is opened and the circuit dynamics is described by
is assumed to vibrate divergently.
As
reaches
, the comparator COMP triggers the monostable multivibrator MM to output an impulse
.
The impulse
closes the IAF switch
and
is reset to the base
instantaneously holding the continuity property of
:
Repeating IAF switching the circuit generate chaos. Using discrete elements such as op-amps, this circuit can be fabricated easily and chaotic behavior can be confirmed experimentally as shown in Fig. 3.
Note that there exist various CSOs with two memory elements: applying the IAF switch to some oscillator (e.g., Wien bridge oscillator ), we obtain a CSO.
Chaotic dynamics
We assume that Equation (1) has unstable complex characteristic root
:
In this case
can vibrate divergently below the threshold
.
The divergent vibration and the IAF switching correspond to stretching and folding mechanisms, respectively, which are fundamental for chaos generation.
Using the following dimensionless variables and parameters:
Equations (1) and (2) are transformed into the following.
where
and
.
This dimensionless equation is characterized by two parameters
and
which can be controlled by
and
, respectively.
This equation can reproduce chaotic attractor as shown in Fig. 4.
Note that the case
governs wider class of CSOs (Mitsubori and Saito 2000).
1D return map
The circuit dynamics can be analyzed using 1-D return map.
Some objects of the map are shown in Fig. 5:
the domain of the map
,
the threshold line
, and
the base line
.
Let a point on these objects be represented by their
-coordinate.
Also let
be a point on
such that a trajectory started from
touches
within half period.
For the case
let a trajectory start from a point
on
at
.
If
, the trajectory return to
at
without reaching
.
If
, the trajectory hits the threshold
and is reset to the base
.
Then the trajectory re-starts from
and returns to
.
Since any trajectory started from
on
must return to
, a 1-D return map can be defined:
where
is the return point on
.
That is, the circuit dynamics can be integrated into the iteration
as shown in Fig. 5.
Using exact piecewise solution of Equation (3), the return map can be described and chaos generation can be guaranteed theoretically (Nakano and Saito 2002) in the sense of ergodic and positive Lyapunov exponent (Lasota and Mackey).
The theoretical results can be extended for the case
and other CSO examples (Mitsubori and Saito 2000).
Further development
The CSO can be developed into a variety of interesting systems:
- 1. If periodic spike-train input is applied, the CSO exhibits rich synchronous/asynchronous phenomena (Miyach, Nakano and Saito 2003)
- 2. If the sub-circuit has two or more memory elements, the IAF switch can cause hyperchaos and rich bifurcation phenomena (Takahashi, Nakano and Saito 2005)
- 3. The PCNN of CSO can exhibits rich periodic/chaotic synchronous phenomena.
Prospective engineering applications include flexible image processing and spike-based communications (Nakano and Saito 2004).
References
- Campbell S. R., Wang D., Jayaprakash C. (1999) Synchrony and desynchrony in integrate-and-fire oscillators, Neural computation, 11, 1595-1619.
- Ekwakil A. S., Kennedy M. P. (2001) Construction of classes of circuit-independent chaotic oscillators using passive-only nonlinear devices, IEEE Trans. Circuits Systs. I, 48, 289-307.
- Hopfield J. J., Herz A. V. M. (1995) Rapid local synchronization of action potentials: toward computation with coupled integrate-and-fire neurons, Proc. Natl. Acad. Sci., 92, 6655-6662.
- Izhikevich E. M. (1999) Weakly Pulse-coupled oscillators, FM Interactions, Synchronization, and oscillatory associative memory, IEEE Trans. Neural Networks, 10, no. 3, 508-526.
- Izhikevich E. M. (2001) Resonate-and-fire neurons, Neural Networks, 14, 883-894.
- Lasota A., Mackey M. C. (1994) Chaos, Fractals, and Noise - Second Edition, Springer-Verlag.
- Matsumoto T., Chua L., Komuro M. (1985) The double scroll, IEEE Trans. Circuits Syst., 32, 8, 797-818.
- Maggio G. M., De Feo O. , Kennedy M. P. (1999) Nonlinear analysis of the Colpitts oscillator and application to design, IEEE Trans. Circuits Systs. I, 46, 9, 1118-1130.
- Maggio G. M., Rulkov N., Reggiani L. (2001) Pseudo-chaotic time hopping for UWB impulse radio. IEEE Trans. Circuits Syst. I, 48, no.12, 1424-1435.
- Mirollo R. E., Strogatz S. H. (1990) Synchronization of pulse-coupled biological oscillators, SIAM J. Appl. Math., 50, 1645-1662.
- Mitsubori K., Saito T. (2000) Mutually pulse-coupled chaotic circuits by using dependent switched capacitors, IEEE Trans. Circuits Syst. I, 47, 10,1469-1478.
- Miyachi K., Nakano H., Saito T. (2003) Response of a simple dependent switched capacitor circuit to a pulse-train input, IEEE Trans. Circuits Syst. I, 50, 9, 1180-1187.
- Nakano H., Saito T. (2002), Basic dynamics from a pulse-coupled network of autonomous integrate-and-fire chaotic circuits, IEEE Trans. Neural Networks, 13, 92-100.
- Nakano H., Saito T. (2004) Grouping synchronization in a pulse-coupled network of chaotic spiking oscillators, IEEE Trans. Neural Networks, 15, 5, 1018-1026.
- Takahashi Y., Nakano H., Saito T. (2005) Hyperchaotic spiking oscillators with periodic pulse-train input, IEEE Trans. Circuits Syst. II, 52, 6, 344-348.
Internal references
- John W. Milnor (2006) Attractor. Scholarpedia, 1(11):1815.
- John Guckenheimer (2007) Bifurcation. Scholarpedia, 2(6):1517.
- James Meiss (2007) Dynamical systems. Scholarpedia, 2(2):1629.
- Christophe Letellier and Otto E. Rossler (2007) Hyperchaos. Scholarpedia, 2(8):1936.
- DeLiang Wang (2006) LEGION: locally excitatory globally inhibitory oscillator networks. Scholarpedia, 1(9):1620.
- Jeff Moehlis, Kresimir Josic, Eric T. Shea-Brown (2006) Periodic orbit. Scholarpedia, 1(7):1358.
- Christophe Letellier and Otto E. Rossler (2006) Rossler attractor. Scholarpedia, 1(10):1721.
- Alain Destexhe (2007) Spike-and-wave oscillations. Scholarpedia, 2(2):1402.
- Philip Holmes and Eric T. Shea-Brown (2006) Stability. Scholarpedia, 1(10):1838.
- Arkady Pikovsky and Michael Rosenblum (2007) Synchronization. Scholarpedia, 2(12):1459.
- Frank Hoppensteadt (2006) Voltage-controlled oscillations in neurons. Scholarpedia, 1(11):1599.
External Links
See Also
Voltage-Controlled Oscillations in Neurons, LEGION: Locally Excitatory Globally Inhibitory Oscillator Networks, Bifurcation, Rossler Attractor, Spike-and-Wave Oscillations
| Toshimichi Saito (2007) Chaotic spiking oscillators. Scholarpedia, 2(9):1831, (go to the first approved version) Created: 4 August 2006, reviewed: 19 September 2007, accepted: 19 September 2007 |
| Action editor: | Dr. Eugene M. Izhikevich, Editor-in-Chief of Scholarpedia, the peer-reviewed open-access encyclopedia |
and E=-0.2V. i is in mA.
and
.
and behaves chaotically.
