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.
6736227
VLSI implementation of an energy-aware wake-up detector for an acoustic surveillance sensor network
We present a low-power VLSI wake-up detector for a sensor network that uses acoustic signals to localize ground-based vehicles. The detection criterion is the degree of low-frequency periodicity in the acoustic signal, and the periodicity is computed from the “bumpiness” of the autocorrelation of a one-bit version of the signal. We then describe a CMOS ASIC that implements the periodicity estimation algorithm. The ASIC is fully functional and its core consumes 835 nanowatts. It was integrated into an acoustic enclosure and deployed in field tests with synthesized sounds and 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.
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.
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.
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.
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.
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.
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.
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.