| 1. |
- Aunet, Snorre, et al.
(författare)
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Real-time reconfigurable subthreshold CMOS perceptron
- 2008
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Ingår i: IEEE Transactions on Neural Networks. - 1045-9227 .- 1941-0093. ; 19:4, s. 645-657
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Tidskriftsartikel (refereegranskat)abstract
- In this paper, a new, real-time reconfigurable perceptron circuit element is presented. A six-transistor version used as a threshold gate, having a fan-in of three, producing adequate outputs for threshold of T = 1, 2 and 3 is demonstrated by chip measurements. Subthreshold operation for supply voltages in the range of 100-350 mV is shown. The circuit performs competitively with a standard static complimentary metal-oxide-semiconductor (CMOS) implementation when maximum speed and energy delay product are taken into account, when used in a ring oscillator. Functionality per transistor is, to our knowledge, the highest reported for a variety of comparable circuits not based on floating gate techniques. Statistical simulations predict probabilities for making working circuits under mismatch and process variations. The simulations, in 120-nm CMOS, also support discussions regarding lower limits to supply voltage and redundancy. A brief discussion on bow the circuit may be exploited as a basic building block for future defect tolerant mixed signal circuits, as well as neural networks, exploiting redundancy, is included.
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| 2. |
- Bodén, Mikael, et al.
(författare)
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On learning context-free and context-sensitive languages
- 2002
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Ingår i: IEEE Transactions on Neural Networks. - New York : IEEE. - 1045-9227 .- 1941-0093. ; 13:2, s. 491-493
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Tidskriftsartikel (refereegranskat)abstract
- The long short-term memory (LSTM) is not the only neural network which learns a context sensitive language. Second-order sequential cascaded networks (SCNs) are able to induce means from a finite fragment of a context-sensitive language for processing strings outside the training set. The dynamical behavior of the SCN is qualitatively distinct from that observed in LSTM networks. Differences in performance and dynamics are discussed.
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| 3. |
- Eklund, Patrik, 1958-, et al.
(författare)
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Neural fuzzy logic programming
- 1992
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Ingår i: IEEE Transactions on Neural Networks. - : Institute of Electrical and Electronics Engineers (IEEE). - 1045-9227 .- 1941-0093. ; 3:5, s. 815-818
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Tidskriftsartikel (refereegranskat)abstract
- A foundational development of propositional fuzzy logic programs is presented. Fuzzy logic programs are structured knowledge bases including uncertainties in rules and facts. The precise specifications of uncertainties has a great influence on the performance of the knowledge base. We show how fuzzy logic programs can be transformed to neural nets, where adaptations of uncertainties in the knowledge base increase the reliability of the program and are carried out automatically.
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| 4. |
- Häkkinen, Jari, et al.
(författare)
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Local routing algorithms based on Potts neural networks.
- 2000
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Ingår i: IEEE Transactions on Neural Networks. - : Institute of Electrical and Electronics Engineers (IEEE). - 1045-9227 .- 1941-0093. ; 11:4, s. 970-977
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Tidskriftsartikel (refereegranskat)abstract
- A feedback neural approach to static communication routing in asymmetric networks is presented, where a mean field formulation of the Bellman-Ford method for the single unicast problem is used as a common platform for developing algorithms for multiple unicast, multicast and multiple multicast problems. The appealing locality and update philosophy of the Bellman-Ford algorithm is inherited. For all problem types the objective is to minimize a total connection cost, defined as the sum of the individual costs of the involved arcs, subject to capacity constraints. The methods are evaluated for synthetic problem instances by comparing to exact solutions for cases where these are accessible, and else with approximate results from simple heuristics. In general, the quality of the results are better than those of the heuristics. Furthermore, the computational demands are modest, even when the distributed nature of the the approach is not exploited numerically.
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| 5. |
- DeWeerth, Stephen P., et al.
(författare)
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A Simple Neuron Servo
- 1991
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Ingår i: IEEE Transactions on Neural Networks. - : Institute of Electrical and Electronics Engineers (IEEE). - 1045-9227. ; 2:2, s. 248-251
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Tidskriftsartikel (refereegranskat)
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| 6. |
- Przybyszewski, A. W., et al.
(författare)
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Basic difference between brain and computer: Integration of asynchronous processes implemented as hardware model of the retina
- 2007
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Ingår i: IEEE Transactions on Neural Networks. - : Institute of Electrical and Electronics Engineers (IEEE). - 1045-9227. ; 18:1, s. 70-85
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Tidskriftsartikel (refereegranskat)abstract
- There exists a common view that the brain acts like a Turing machine: The machine reads information from an infinite tape (sensory data) and, on the basis of the machine's state and information from the tape, an action (decision) is made. The main problem with this model lies in how to synchronize a large number of tapes in an adaptive way so that the machine is able to accomplish tasks such as object classification. We propose that such mechanisms exist already in the eye. A popular view is that the retina, typically associated with high gain and adaptation for light processing, is actually performing local preprocessing by means of its center-surround receptive field. We would like to show another property of the retina: The ability to integrate many independent processes. We believe that this integration is implemented by synchronization of neuronal oscillations. In this paper, we present a model of the retina consisting of a series of coupled oscillators which can synchronize on several scales. Synchronization is an analog process which is converted into a digital spike train in the output of the retina. We have developed a hardware implementation of this model, which enables us to carry out rapid simulation of multineuron oscillatory dynamics. We show that the properties of the spike trains in our model are similar to those found in vivo in the cat retina.
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