719681
Feature competition in a spike-based winner-take-all VLSI network
Recurrent networks and hardware analogs that perform a winner-take-all computation have been studied extensively. This computation is rarely demonstrated in a spiking network of neurons receiving input spike trains. In this work, we demonstrate this computation not only within a VLSI network but also across networks of integrate-and-fire neurons in a feature competition task. The chip has four populations of neurons receiving input spike trains that represent the outputs of four feature maps. The connectivity within each population is configured so that all the neurons compete with one another. In addition, a second level of competition, which we call the feature competition, can be introduced between all populations (or feature maps). The two levels of competition are useful in a system that has to select both the locations of relevant features and the best feature map that is coded in an input stimulus. The selection process can be completed as fast as after two input spikes
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.
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>>
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.
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.
1673600
Inferring Data Transformation Rules to Integrate Semantic Web Services
OWL-S allows selecting, composing and invoking Web Services at different levels of abstraction: selection uses high level abstract descriptions, invocation uses low level grounding ones, while composition needs to consider both high and low level descriptions. In our setting, two Web Services are to be composed so that output from the upstream one is used to create input for the downstream one. These Web Services may have different data models but are related to each other through high and low level descriptions. 
 
Correspondences must be found between components of the upstream data type and the downstream ones. Low level data transformation functions may be required (e.g. unit conversions, data type conversions). The components may be arranged in different XML tree structures. Thus, multiple data transformations are necessary: reshaping the message tree, matching leaves by corresponding types, translating through ontologies, and calling conversion functions. Our prototype compiles these transformations into a set of data transformation rules, using our tableau-based ALC Description Logic reasoner to reason over the given OWL-S and WSDL descriptions, as well as the related ontologies. A resolution-based inference mechanism for running these rules is embedded in an inference queue that conducts data from the upstream to the downstream service, running the rules to perform the data transformation in the process.
1315911
An Object Semantic Model of SOFL
SOFL (Structured-Object-based-Formal Language) is recently proposed to combine the advantages of formal methods, structured methods and object-oriented methodology into one method for software development. SOFL integrates modeling techniques from VDM (for specifying system component state) and data flow diagrams with Petri nets (for specifying system behaviours and interaction). To support the standardisation and the tool support for SOFL, a formal semantics of the language is desirable. As SOFL is under further development, the semantic representation of current SOFL needs to be easily reused and extended. In this paper, an object-oriented approach is taken to specify the semantics of SOFL and this approach is proved to be effective in providing a modular and reusable semantic representation. Object modeling techniques, such as inheritance is used to illustrate the common and the differences between various SOFL graphical constructs; object containment is used to capture the acyclic structure of SOFL hierarchical module decomposition.
8071150
TCP-Illinois: A loss- and delay-based congestion control algorithm for high-speed networks
We introduce a new congestion control algorithm for high-speed networks, called TCP-Illinois. TCP-Illinois uses packet loss information to determine whether the window size should be increased or decreased, and uses queueing delay information to determine the amount of increment or decrement. TCP-Illinois achieves high throughput, allocates the network resource fairly, and is incentive compatible with standard TCP. We also build a new stochastic matrix model, capturing standard TCP and TCP-Illinois as special cases, and use this model to analyze their fairness properties for both synchronized and unsynchronized backoff behaviors. We finally perform simulations to demonstrate the performance of TCP-Illinois.
18693305
Verifying Consistency and Validity of Formal Specifications by Testing
Detecting faults in specifications can help reduce the cost and risk of software development because incorrect implementation can be prevented early. This goal can be achieved by verifying the consistency and validity of specifications. In this paper we put forward specification testing as a practical technique for verification and validation of formal specifications. Our approach is to derive proof obligations from a specification and then test them, in order to detect faults leading to the violation of consistency or validity of the specification. We describe proof obligations for various consistency properties of a specification, and suggest the use of five strategies for testing them. We provide a method for testing implicit specifications by evaluation rather than by prototyping, and criteria for interpreting the meaning of test results.
11127695
The semantics of extended SOFL
SOFL (structured-object-based-formal language) has been extended to a formal object-oriented language and method while keeping its structured features. This extension allows powerful object-oriented reuse mechanisms, such as class inheritance and object composition, to be utilized in the early design phases. This paper presents the semantics for this extended SOFL, and further demonstrates the extendibility and reusability of the object-oriented semantic models of SOFL.