12793172
Continuous-time adaptive delay system
We have developed an adaptive delay system that adjusts the delay of a delay element so that it matches the temporal disparity between the onset of two input signals. The delay is controlled either by an external bias voltage, or by an intrinsic signal derived from an adaptive block. The operation of the adaptive delay system is similar to that of a charge-pump phase-lock loop, with an extended lock-in range of more than 5 decades. Standard CMOS transistors are used in their subthreshold region. Experimental results from circuits fabricated in 2 /spl mu/m CMOS technology are in agreement with the analysis.<<ETX>>
34951314
Spike synchronization in a network of silicon integrate-and-fire neurons
Spike-event based computational processing by neuronal networks depends on a variety of spatio-temporal mechanisms that are distributed across neuronal synapses, dendrites, and somata. The overall processing of spatio-temporal patterns of spike requires global temporal coherence between all these processes both within a neuron, and across all neurons of the network. We are evaluating the use of networks of hybrid analog-digital integrate-and-fire neurons, fabricated using VLSI, for studying real-time event-based processing. These hardware networks have the advantages of real-time operation, and inherent global synchronization by their analog implementation. However, one of the technical challenges in the operation of such networks is the unavoidable fabrication related variance between the different neurons of the network. Here we show that despite this variance, an important behavior of neuronal networks, spike synchronization, can be obtained from a simple network of VLSI neurons interconnected by lateral excitation and global inhibition.
6979172
Encoding the Temporal Statistics of Markovian Sequences of Stimuli in Recurrent Neuronal Networks
Encoding, storing, and recalling a temporal sequence of stimuli in a neuronal network can be achieved by creating associations between pairs of stimuli that are contiguous in time. This idea is illustrated by studying the behavior of a neural network model with binary neurons and binary stochastic synapses. The network extracts in an unsupervised manner the temporal statistics of the sequence of input stimuli. When a stimulus triggers the recalling process, the statistics of the output patterns reflects those of the input. If the sequence of stimuli is generated through a Markov process, then the network dynamics faithfully reproduces all the transition probabilities.
18592302
A Winner-Take-All Circuit with Controllable Soft Max Property
I describe a silicon network consisting of a group of excitatory neurons and a global inhibitory neuron. The output of the inhibitory neuron is normalized with respect to the input strengths. This output models the normalization property of the wide-field direction-selective cells in the fly visual system. This normalizing property is also useful in any system where we wish the output signal to code only the strength of the inputs, and not be dependent on the number of inputs. The circuitry in each neuron is equivalent to that in Lazzaro's winner-take-all (WTA) circuit with one additional transistor and a voltage reference. Just as in Lazzaro's circuit, the outputs of the excitatory neurons code the neuron with the largest input. The difference here is that multiple winners can be chosen. By varying the voltage reference of the neuron, the network can transition between a soft-max behavior and a hard WTA behavior. I show results from a fabricated chip of 20 neurons in a 1.2 µm CMOS technology.
1845062
Adaptive Retina with Center-Surround Receptive Field
Both vertebrate and invertebrate retinas are highly efficient in extracting contrast independent of the background intensity over five or more decades. This efficiency has been rendered possible by the adaptation of the DC operating point to the background intensity while maintaining high gain transient responses. The center-surround properties of the retina allows the system to extract information at the edges in the image. This silicon retina models the adaptation properties of the receptors and the antagonistic center-surround properties of the laminar cells of the invertebrate retina and the outer-plexiform layer of the vertebrate retina. We also illustrate the spatio-temporal responses of the silicon retina on moving bars. The chip has 59×64 pixels on a 6.9×6.8mm2 die and it is fabricated in 2 µm n-well technology.
6161480
Homeostasis in a Silicon Integrate and Fire Neuron
In this work, we explore homeostasis in a silicon integrate-and-fire neuron. The neuron adapts its firing rate over long time periods on the order of seconds or minutes so that it returns to its spontaneous firing rate after a lasting perturbation. Homeostasis is implemented via two schemes. One scheme looks at the presynaptic activity and adapts the synaptic weight depending on the presynaptic spiking rate. The second scheme adapts the synaptic "threshold" depending on the neuron's activity. The threshold is lowered if the neuron's activity decreases over a long time and is increased for prolonged increase in postsynaptic activity. Both these mechanisms for adaptation use floating-gate technology. The results shown here are measured from a chip fabricated in a 2-µm CMOS process.
383574
A simulation approach to verification and validation of formal specifications
Specification simulation is an approach to verifying and validating specifications by well-selected sample data. In this paper we put forward a technique for simulation of formal specifications in order to detect potential faults and validate their desired functions. The important benefit of this technique is it allows us to simulate implicit specifications, which are usually defined with a pair of pre- and postconditions and may not be executable. We discuss ways of simulation case generation, evaluation of logical expressions, and simulation result analysis, and demonstrate how they are applied in practice by examples.
9811887
A formal operational semantics for SOFL
SOFL (Structured-Object-Based-Formal Language) is a formal language and method for practical systems development. As a language, it integrates data flow diagrams, VDM-SL, and Petri nets to provide a graphical and textual formal notation for specification construction. Previous publications introducing SOFL are based on its informal semantics. We provide a formal operational semantics which gives a firm foundation for consistent understanding and application of SOFL in practical systems development. Development of the semantics, and application of SOFL to practical systems, have led to some changes in the original definitions. This formal semantics will serve as a firm foundation for building an effective support environment for SOFL.
14203644
Word sense disambiguation in queries
This paper presents a new approach to determine the senses of words in queries by using WordNet. In our approach, noun phrases in a query are determined first. For each word in the query, information associated with it, including its synonyms, hyponyms, hypernyms, definitions of its synonyms and hyponyms, and its domains, can be used for word sense disambiguation. By comparing these pieces of information associated with the words which form a phrase, it may be possible to assign senses to these words. If the above disambiguation fails, then other query words, if exist, are used, by going through exactly the same process. If the sense of a query word cannot be determined in this manner, then a guess of the sense of the word is made, if the guess has at least 50% chance of being correct. If no sense of the word has 50% or higher chance of being used, then we apply a Web search to assist in the word sense disambiguation process. Experimental results show that our approach has 100% applicability and 90% accuracy on the most recent robust track of TREC collection of 250 queries. We combine this disambiguation algorithm to our retrieval system to examine the effect of word sense disambiguation in text retrieval. Experimental results show that the disambiguation algorithm together with other components of our retrieval system yield a result which is 13.7% above that produced by the same system but without the disambiguation, and 9.2% above that produced by using Lesk's algorithm. Our retrieval effectiveness is 7% better than the best reported result in the literature.
5842197
Configurable indexing and ranking for XML information retrieval
Indexing and ranking are two key factors for efficient and effective XML information retrieval. Inappropriate indexing may result in false negatives and false positives, and improper ranking may lead to low precisions. In this paper, we propose a configurable XML information retrieval system, in which users can configure appropriate index types for XML tags and text contents. Based on users' index configurations, the system transforms XML structures into a compact tree representation, Ctree, and indexes XML text contents. To support XML ranking, we propose the concepts of "weighted term frequency" and "inverted element frequency," where the weight of a term depends on its frequency and location within an XML element as well as its popularity among similar elements in an XML dataset. We evaluate the effectiveness of our system through extensive experiments on the INEX 03 dataset and 30 content and structure (CAS) topics. The experimental results reveal that our system has significantly high precision at low recall regions and achieves the highest average precision (0.3309) as compared with 38 official INEX 03 submissions using the strict evaluation metric.
2425320
Scalable data aggregation for dynamic events in sensor networks
Computing and maintaining network structures for efficient data aggregation incurs high overhead for dynamic events where the set of nodes sensing an event changes with time. Moreover, structured approaches are sensitive to the waiting-time which is used by nodes to wait for packets from their children before forwarding the packet to the sink. Although structureless approaches can address these issues, the performance does not scale well with the network size. We propose a semi-structured approach that uses a structureless technique locally followed by Dynamic Forwarding on an implicitly constructed packet forwarding structure to support network scalability. The structure, ToD, is composed of multiple shortest path trees. After performing local aggregation, nodes dynamically decide the forwarding tree based on the location of the sources. The key principle behind ToD is that adjacent nodes in a graph will have low stretch in one of these trees in ToD, thus resulting in early aggregation of packets. Based on simulations on a 2000 nodes network and real experiments on a 105 nodes Mica2-based network, we conclude that efficient aggregation in large scale networks can be achieved by our semi-structured approach.