6053956
A low-power correlation-derivative CMOS VLSI circuit for bearing estimation
We present a CMOS integrated circuit (IC) for bearing estimation in the low-audio range that performs a correlation derivative approach in a 0.35-/spl mu/m technology. The IC calculates the bearing angle of a sound source with a mean variance of one degree in a 360/spl deg/ range using four microphones: one pair is used to produce the indication and the other to define the quadrant. An adaptive algorithm decides which pair to use depending on the direction of the incoming signal, in such a way to obtain the best estimate. The IC contains two blocks with 104 stages each. Every stage has a delay unit, a block to reduce the clock speed, and a 10-bit UP/DN counter. The IC measures 2 mm by 2.4 mm, and dissipates 600 /spl mu/W at 3.3 V and 200 kHz. It is purely digital and uses a one-bit quantization of the input signals.
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.
36729490
Energy efficiency in a channel model for the spiking axon
Abstract We examine the spiking axon as a communication channel. We develop a first principles channel model that encompasses the noise in the axon, which manifests itself as spike jitter, and the power consumption, which arises from the activity of the Na + –K + pump. This model enables us to examine the trade-off between the information rate and power consumption. Using parameters from the frog myelinated axon, we determine the spike rate that corresponds to the maximum energy efficiency. This spike rate is consistent with experimental observations, which suggests that neural communication may have developed to maximize energy efficiency rather than information rate alone.
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.
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.
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.
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.
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.
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.