7913359
Probabilistic synaptic weighting in a reconfigurable network of VLSI integrate-and-fire neurons
We present a scheme for implementing highly-connected, reconfigurable networks of integrate-and-fire neurons in VLSI. Neural activity is encoded by spikes, where the address of an active neuron is communicated through an asynchronous request and acknowledgement cycle. We employ probabilistic transmission of spikes to implement continuous-valued synaptic weights, and memory-based look-up tables to implement arbitrary interconnection topologies. The scheme is modular and scalable, and lends itself to the implementation of multi-chip network architectures. Results from a prototype system with 1024 analog VLSI integrate-and-fire neurons, each with up to 128 probabilistic synapses, demonstrate these concepts in an image processing task.
14474778
Spike Timing-Dependent Plasticity in the Address Domain
Address-event representation (AER), originally proposed as a means to communicate sparse neural events between neuromorphic chips, has proven efficient in implementing large-scale networks with arbitrary, configurable synaptic connectivity. In this work, we further extend the functionality of AER to implement arbitrary, configurable synaptic plasticity in the address domain. As proof of concept, we implement a biologically inspired form of spike timing-dependent plasticity (STDP) based on relative timing of events in an AER framework. Experimental results from an analog VLSI integrate-and-fire network demonstrate address domain learning in a task that requires neurons to group correlated inputs.
10633458
Field test results for low power bearing estimator sensor nodes
The paper describes experimental results of low power sensor nodes designed to perform bearing estimation. The nodes are intended to form a wireless sensor network able to locate an audio source. Two different nodes are tested: one is based on a cross-correlation derivative integrated circuit (IC), and the other on a gradient flow IC. Implementation details and experimental results of both systems working in a natural environment are presented.
2599649
A wake-up detector for an acoustic surveillance sensor network: algorithm and VLSI implementation
We describe a low-power VLSI wake-up detector for use in an acoustic surveillance sensor network. The detection criterion is based on the degree of low-frequency periodicity in the acoustic signal. To this end, we have developed a periodicity estimation algorithm that maps particularly well to a low-power VLSI implementation. The time-domain algorithm is based on the "bumpiness" of the autocorrelation of one-bit version of the signal. We discuss the relationship of this algorithm to the maximum-likelihood estimator for periodicity. We then describe a full-custom CMOS ASIC that implements this algorithm. This ASIC is fully functional and its core consumes 835 nanoWatts. The ASIC was integrated into an acoustic enclosure and tested outdoors on synthesized sounds. This unit was also deployed in a three-node sensor network and tested on ground-based vehicles.
36350590
Spike communication of dynamic stimuli: rate decoding versus temporal decoding
Abstract We compare two methods for extracting information about a dynamic analog stimulus from a spike train: a rate decoder, which is based on the number of spikes in a counting window, and a temporal decoder, which is based on interspike intervals. We derive analytical expressions for the distortion between a stimulus current that drives an integrate-and-fire spike generator and a reconstruction of that current based on the spike train. We consider intrinsic distortion, which arises due to the limitations of spike coding, and extrinsic distortion, which is due to explicit alterations of the spike train. We find that in the absence of extrinsic distortion, the temporal decoder is superior to the rate decoder. In the presence of extrinsic distortion, the temporal decoder is preferred when low latency is required, but the rate decoder is preferred when the latency requirement is relaxed.
16600244
Heterogeneous integration of biomimetic acoustic microsystems
We discuss biologically inspired devices and architectures for acoustic processing microsystems. We exploit state of the art integrated microsystems technologies to heterogeneously integrate electronics and micromechanical structures for acoustic sensing and signal processing.
33407352
Document image matching and annotation lifting
Two images of the same document could differ significantly due to faxing, scanner distortions, or degradation through multigeneration copying. Additionally, one of the images may have extensive annotations not present in the other. We give a method for registering two such images and separating out annotations. We further present an algorithm for detecting and repairing broken strokes in the annotations. Our methods have been tested on a wide variety of documents with reliable results; for the special case of form dropout our results are better than had been obtained previously with special-purpose algorithms.
8685428
Continuous queries over append-only databases
In a database to which data is continually added, users may wish to issue a permanent query and be notified whenever data matches the query. If such continuous queries examine only single records, this can be implemented by examining each record as it arrives. This is very efficient because only the incoming record needs to be scanned. This simple approach does not work for queries involving joins or time. The Tapestry system allows users to issue such queries over a database of mail and bulletin board messages. The user issues a static query, such as “show me all messages that have been replied to by Jones,” as though the database were fixed and unchanging. Tapestry converts the query into an incremental query that efficiently finds new matches to the original query as new messages are added to the database. This paper describes the techniques used in Tapestry, which do not depend on triggers and thus be implemented on any commercial database that supports SQL. Although Tapestry is designed for filtering mail and news messages, its techniques are applicable to any append-only database.
1562350
Constructing Comparative Genome Maps with Unresolved Marker Order
Comparative genome maps are a powerful tool for interpreting the genomes of related organisms. The species maps which are the input to the process of constructing comparative maps are often themselves constructed from incomplete or inconsistent data, resulting in markers (or genes) whose order is not fully resolved. This incomplete marker order information is often handled by placing markers whose relative order cannot be reliably inferred together in a bin which is mapped to a common location. Previous automated and manual methods have handled such markers in an ad hoc or arbitrary way. We present efficient algorithms for comparative map construction that provide a principled method for handling unresolved marker order. The algorithms are based on a technique for efficiently computing a marker order that optimizes a natural parsimony criterion; in this way, they also yield a working hypothesis about the original incomplete data set.
654791
An image signature for any kind of image
We describe an algorithm for computing an image signature, suitable for first-stage screening for duplicate images. Our signature relies on the relative brightness of image regions, and is generally applicable to photographs, text documents, and line art. We give experimental results on the sensitivity and robustness of signatures for actual image collections, and also results on the robustness of signatures under transformations such as resizing, rescanning, and compression.
4796791
A global approach to automatic solution of jigsaw puzzles
We present a new algorithm for automatically solving jigsaw puzzles by shape alone. The algorithm can solve more difficult puzzles than could be solved before, without the use of backtracking or branch-and-bound. The algorithm can handle puzzles in which pieces border more than four neighbors, and puzzles with as many as 200 pieces. Our overall strategy follows that of previous algorithms but applies a number of new ideas, such as robust fiducial points, "highest- confidence-first" search, and frequent global reoptimization of partial solutions.