30699245
A low-power CMOS integrated circuit for bearing estimation
We present the design and testing of a micropower integrated circuit for the estimation of the bearing angle of a sound source with respect to a pair of microphones. The algorithm is based on a modified binary cross-correlation approach suitable for low-power operation. The circuit has been tested and operates at 600 /spl mu/W at performance levels matching theoretical simulations.
8543826
Analog VLSI spiking neural network with address domain probabilistic synapses
We present an analog VLSI address-event transceiver containing an array of integrate-and-fire neurons and a scheme for implementing a reconfigurable neural network with probabilistic synapses. Neural "spikes" are transmitted through address-event representation-the address of the sending neuron is communicated through an asynchronous request and acknowledgment cycle. Continuous-valued synaptic weights are implemented by probabilistically routing address events. 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 application.
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.
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.
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.
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.
2216158
Automatic Quality Assessment of Peptide Tandem Mass Spectra
MOTIVATION
A powerful proteomics methodology couples high-performance liquid chromatography (HPLC) with tandem mass spectrometry and database-search software, such as SEQUEST. Such a set-up, however, produces a large number of spectra, many of which are of too poor quality to be useful. Hence a filter that eliminates poor spectra before the database search can significantly improve throughput and robustness. Moreover, spectra judged to be of high quality, but that cannot be identified by database search, are prime candidates for still more computationally intensive methods, such as de novo sequencing or wider database searches including post-translational modifications.


RESULTS
We report on two different approaches to assessing spectral quality prior to identification: binary classification, which predicts whether or not SEQUEST will be able to make an identification, and statistical regression, which predicts a more universal quality metric involving the number of b- and y-ion peaks. The best of our binary classifiers can eliminate over 75% of the unidentifiable spectra while losing only 10% of the identifiable spectra. Statistical regression can pick out spectra of modified peptides that can be identified by a de novo program but not by SEQUEST. In a section of independent interest, we discuss intensity normalization of mass spectra.
26906105
Trustworthy Paper Documents
In the first part of this paper, we propose a watermarking method for text documents that is less vulnerable to attacks than previous methods. In the second part, we propose a method for protecting the actual content of the document. In a section of independent interest, we discuss the interplay between error-correcting codes and steganography.
46268673
EigenMS: De Novo Analysis of Peptide Tandem Mass Spectra by Spectral Graph Partitioning
We report on a new de novo peptide sequencing algorithm that uses spectral graph partitioning. In this approach, relationships between m/z peaks are represented by attractive and repulsive springs, and the vibrational modes of the spring system are used to infer information about the peaks (such as “likely b-ion” or “likely y-ion”). We demonstrate the effectiveness of this approach by comparison with other de novo sequencers on test sets of ion-trap and QTOF spectra, including spectra of mixtures of peptides. On all data sets we outperform the other sequencers. Along with spectral graph theory techniques, EigenMS incorporates another improvement of independent interest: robust statistical methods for recalibration of time-of-flight mass measurements. Robust recalibration greatly outperforms simple least-squares recalibration, achieving about three times the accuracy for one QTOF data set.
9584467
Improved Ranking Functions for Protein and Modification-Site Identifications
There are a number of computational tools for assigning identifications to peptide tandem mass spectra, but many fewer tools for the crucial next step of integrating spectral identifications into higher-level identifications, such as proteins or modification sites. Here we describe a new program called ComByne for scoring and ranking higher-level identifications. We compare ComByne to existing algorithms on several complex biological samples, including a sample of mouse blood plasma spiked with known concentrations of human proteins. A Web interface to our software is at http://bio.parc.xerox.com.