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[PDF] Top 20 Spike sorting with Gaussian mixture models

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Spike sorting with Gaussian mixture models

Spike sorting with Gaussian mixture models

... classifying spike waveforms into their underlying neuronal sources remains a ...called spike sorting, typically consists of two steps: (1) extracting relevant waveform features ...of Gaussian ... See full document

14

Spatial interpolation and geostatistic simulation with the incremental Gaussian mixture network

Spatial interpolation and geostatistic simulation with the incremental Gaussian mixture network

... deal with spatially corre- lated ...Sequential Gaussian Simulation (SGS) are two examples of traditional geostatistical tools used for these kinds of ...familiarity with the ...traditional ... See full document

77

Real-time unsupervised motion learning for autonomous underwater vehicles using gaussian mixture models

Real-time unsupervised motion learning for autonomous underwater vehicles using gaussian mixture models

... deal with real-time ...finite mixture as soon as a new sample is observed, and meanwhile does not need to store the large number of data samples that is indispensable for batch learning ...dealing ... See full document

92

Signal Partitioning Algorithm for Highly Efficient Gaussian Mixture Modeling in Mass Spectrometry.

Signal Partitioning Algorithm for Highly Efficient Gaussian Mixture Modeling in Mass Spectrometry.

... approach with many potential applications includ- ing peak detection and quantification, smoothing, de-noising, feature extraction and spec- tral signal ...of mixture modeling of mass spectra of ... See full document

19

Mixture models in quantitative genetics and applications to animal breeding

Mixture models in quantitative genetics and applications to animal breeding

... a Gaussian mixture with random effects using the EM algorithm with a Monte-Carlo ...2-component mixture model (with thousands of random effects), and retrieved accurate estimates ... See full document

13

Gaussian mixture modeling of hemispheric lateralization for language in a large sample of healthy individuals balanced for handedness.

Gaussian mixture modeling of hemispheric lateralization for language in a large sample of healthy individuals balanced for handedness.

... relationships with manual preference and manual preference strength were studied in a sample of 297 subjects, including 153 left-handers ...compared with a covert word list ...a mixture of 3 and 4 ... See full document

14

Noise-Robust Speaker Recognition using Reduced Multiconditional Gaussian Mixture Models

Noise-Robust Speaker Recognition using Reduced Multiconditional Gaussian Mixture Models

... mismatches with respect to the training audio ...model with only four selected noise conditions is sufficient to provide a level of noise robustness very close to that achieved by the full eight condition ... See full document

10

Gaussian mixture model of heart rate variability.

Gaussian mixture model of heart rate variability.

... univariate models are well suited to problems with stationary ...state-space models with switching dynamics (multiprocess dynamic linear models) can be ...switching models a ... See full document

9

MR-based pseudo-CT generation using water-fat decomposition and Gaussian mixture regression

MR-based pseudo-CT generation using water-fat decomposition and Gaussian mixture regression

... However, with real-world multidimensional data, it can be difficult to know how many components should be ...different models and choose the one that performs best [78] ... See full document

71

Detecting periodicities with Gaussian processes

Detecting periodicities with Gaussian processes

... the Gaussian process approach show a strong periodic signal (we have for all genes S = ...(0.01)) with sharp ...associated with each spike, which ensures that the behaviour of the ... See full document

18

Image Segmentation by Using Finite Bivariate Doubly Truncated Gaussian Mixture Model

Image Segmentation by Using Finite Bivariate Doubly Truncated Gaussian Mixture Model

... [8] With the progress in research on Gaussian mixture models, image segmentation based on Gaussian mixture models has also become very ...through Gaussian ... See full document

10

Non-Gaussian Stochastic Volatility Model with Jumps via Gibbs Sampler

Non-Gaussian Stochastic Volatility Model with Jumps via Gibbs Sampler

... Other models such as the one developed by Warty, Lopes and Polson (2014) [26] brings some innovations by using State Space Models (SSM) and sequen- tial MCMC methods in order to model the returns, allowing ... See full document

79

VOICE RECOGNITION USING ARTIFICIAL NEURAL NETWORKS AND GAUSSIAN MIXTURE MODELS

VOICE RECOGNITION USING ARTIFICIAL NEURAL NETWORKS AND GAUSSIAN MIXTURE MODELS

... recognition. With the advent of technology, the idea of using the voice signals for the purpose of identification has found many useful applications in platforms such as access control of information, access to ... See full document

10

Automatic speaker recognition with Multi-resolution Gaussian Mixture models (MR-GMMs)

Automatic speaker recognition with Multi-resolution Gaussian Mixture models (MR-GMMs)

... Multi-resolution Gaussian Mixture Models, or MR-GMMs, proposed in this study proved to be an effective alternative for developing high–per- formance automatic speaker recognition systems with ... See full document

13

Current Transformer Saturation Detection Using Gaussian Mixture Models

Current Transformer Saturation Detection Using Gaussian Mixture Models

... of mixture components that yields the highest discriminative accuracy for the test data ...few mixture components can yield a GMM which does not accurately model the distinguishing characteristics of ... See full document

9

PREDICTIVE ANALYTICS VIA GAUSSIAN PROCESSES AND STATISTICAL AUDIT VIA GAUSSIAN MIXTURES IN

PREDICTIVE ANALYTICS VIA GAUSSIAN PROCESSES AND STATISTICAL AUDIT VIA GAUSSIAN MIXTURES IN

... The statistical filter developed in this work models a generative underlying pdf that governs the observed data set as a mixture of Gaussians. When applied to the real world data, the filter successfully ... See full document

87

Mixture models of geometric distributions in genomic analysis of inter-nucleotide distances

Mixture models of geometric distributions in genomic analysis of inter-nucleotide distances

... estimated mixture, the random background, the baseline and the empirical distribution are compared for each ...proposed mixture model does not fit to the InD, it may predict genome-wide characteristics ... See full document

21

Spectral analysis of input spike trains by spike-timing-dependent plasticity.

Spectral analysis of input spike trains by spike-timing-dependent plasticity.

... spiking, spike patterns and oscillatory spike ...used models of pairwise STDP. For a single neuron with plastic excitatory synapses, we show how STDP performs a spectral analysis on the ... See full document

22

Spike correlations in a songbird agree with a simple markov population model.

Spike correlations in a songbird agree with a simple markov population model.

... associated with one of 100 song-related activity ...probabilistic models as ours have the advantage that they are closely related to some machine learning algorithms ...[28]. With the growing notion ... See full document

12

Review: Her (Spike Jonze)

Review: Her (Spike Jonze)

... Prije ulaska u kino- svijet, ovaj je autor bio tek dio novog vala mladih video- a tista koji su poetiku spoto a uči ili uz udlji i edije , pa i u jet ičko sto... Njezi je doži lj[r] ... See full document

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