CONDUCTIVITY SPECTRA OF ROCKS FROM THE CRAIGMONT ORE ENVIRONMENT

Geophysics ◽  
1964 ◽  
Vol 29 (5) ◽  
pp. 832-847 ◽  
Author(s):  
D. C. Fraser ◽  
N. B. Keevil ◽  
S. H. Ward
Keyword(s):  
Spectral Analysis ◽  
Induced Polarization ◽  
Frequency Spectra ◽  
Specular Hematite ◽  
Conductivity Spectra

The conductivities of rocks of a suite from the Craigmont ore environment were studied as functions of frequency over the four decades 1,000 to 0.1 cps. The following were observed on a plot of linear conductivity vs log frequency. (1) Rocks mineralized with disseminated sulfides and magnetite yield low‐to‐moderate induced polarization (I.P.) and have conductivity‐frequency spectra which are concave‐up. (2) As veining increases, the spectra tend to straighten, and become sensibly straight when much of the metallics are interconnected; such rocks are characterized by low to large I.P. (3) Massive specular hematite cores yield a large I.P. and have spectra which are markedly concave‐up. For comparison, (4) clay‐containing sandstones yield low to moderate I.P. and have spectra which are slightly convex‐up. Consequently, the combination of I.P. magnitude and spectral analysis permits distinction of the various mineralization types.

scholarly journals MSBE Analysis with Frequency Spectra for Automated Identification of Epileptic Seizure

2019 ◽  
Vol 8 (12) ◽  
pp. 5869-5874
Keyword(s):  
Spectral Analysis ◽  
Seizure Detection ◽  
Detection Technique ◽  
Discriminative Power ◽  
Entropy Analysis ◽  
Analysis Method ◽  
Automated Identification ◽  
Frequency Spectra ◽  
Multi Scale ◽  
Spectral Analysis Method

Objective-This study introduces a reliable automated seizure detection technique based on MSBE (Multi scale bubble entropy) and frequency spectral analysis. Method- This paper aims to develop a novel seizure detection technique that incorporates AM FM model for decomposition of EEG into different sub bands. In our approach, integrated feature set is constructed using multi scale bubble entropy analysis at each sub band and frequency spectral analysis at each electrode. Result-In this paper, an application of bubble entropy with different frequency parameter such as PPF and PSD is provided in order to access its stable and outstanding performance on epileptic seizer detection. The experimental results show that classification accuracy is improved with this algorithm. These finding suggest that extracted features can be used for treatment of epilepsy. Significance- This method provides greater stability and discriminative power, so this technique could be used to detect wider range of seizures.

scholarly journals Accessible Spectrum Analyser

2016 ◽  
Author(s):  
Fiore Martin ◽  
Oussama Metatla ◽  
Nick Bryan-Kinns ◽  
Tony Stockman
Keyword(s):  
Spectral Analysis ◽  
Open Source ◽  
Design Patterns ◽  
Visually Impaired ◽  
Line Of Sight ◽  
Project Design ◽  
Frequency Spectra ◽  
Spectrum Analyser

This paper presents the Accessible Spectrum Analyser (ASA) developed as part of the DePic project (Design Patterns for Inclusive collaboration) at Queen Mary University of London. The ASA uses sonification to provide an accessible representation of frequency spectra to visually impaired audio engineers. The software is free and open source and is distributed as a VST plug-in under OSX and Windows. The aim of reporting this work at the ICAD 2016 conference is to solicit feedback about the design of the present tool and its more generalized counterpart, as well as to invite ideas for other possible applications where it is thought that auditory spectral analysis may be useful, for example in situations where line of sight is not always possible.

Spectral analysis of time domain induced polarization waveforms

2020 ◽  
Vol 177 ◽  
pp. 104037
Author(s):  
Sara Johansson ◽  
Per Hedblom ◽  
Torleif Dahlin
Keyword(s):  
Spectral Analysis ◽  
Time Domain ◽  
Induced Polarization

Relaxation time distribution obtained from a Debye decomposition of spectral induced polarization data

Geophysics ◽  
2016 ◽  
Vol 81 (2) ◽  
pp. E129-E138 ◽  
Author(s):  
Andrea Ustra ◽  
Carlos Alberto Mendonça ◽  
Dimitrios Ntarlagiannis ◽  
Lee D. Slater
Keyword(s):  
Relaxation Time ◽  
Time Distribution ◽  
Relaxation Times ◽  
Induced Polarization ◽  
Complex Conductivity ◽  
Alternative Formulation ◽  
Conductivity Method ◽  
Relaxation Time Distribution ◽  
Spectral Induced Polarization ◽  
Conductivity Spectra

We have developed an alternative formulation for Debye decomposition of complex electric conductivity spectra, by recasting it into a new set of parameters with a close relationship to the continuous formulation for the complex conductivity method. The procedure determines a relaxation time distribution (RTD) and two frequency-independent parameters that modulate the complex conductivity spectra. These two parameters represent (1) the direct current contribution and (2) the conductivity range spanned by the low- and high-frequency limits. The distribution of relaxation times quantifies the contribution of each distinct relaxation process. Assuming that characteristic times with insignificant contributions can be ignored, a minimum set of characteristic relaxation times is determined. Each contribution can then be associated with specific polarization processes that can be interpreted in terms of electrochemical or interfacial parameters of mechanistic models derived from inverted parameters obtained from the proposed approach. Synthetic tests show that the procedure can fit spectral induced polarization (SIP) data and successfully retrieve the RTD. We have applied the procedure to laboratory SIP data from experiments with sand and oil mixtures undergoing microbial degradation of hydrocarbons. The RTD reveals evidence of a length scale at which a new polarization process takes place as a result of the biodegradation process.

Inapplicability of pulse train time‐domain measurements to spectral induced polarization

Geophysics ◽  
1984 ◽  
Vol 49 (6) ◽  
pp. 826-827 ◽  
Author(s):  
Heikki Soininen
Keyword(s):  
Time Domain ◽  
Pulse Train ◽  
Apparent Resistivity ◽  
Single Pulse ◽  
Induced Polarization ◽  
Spectral Measurements ◽  
Frequency Spectra ◽  
Voltage Transient ◽  
The Fourier Transform ◽  
The Time Domain

The method of induced polarization (IP) is based on the frequency dependence of resistivity of rocks. In spectral IP the apparent resistivity is measured at a wide‐frequency band (e.g., 1/1024…4096 Hz). The apparent resistivity depends upon the distribution of the resistivity of the earth according to the laws of electromagnetism. On the basis of their spectral measurements Pelton et al. (1978) proposed that variations in mineral texture give rise to variations in the frequency spectra of resistivity. It should thus be feasible to use these spectra to discriminate between, say, graphite and sulfides. The frequency domain and the time domain are equivalent in a linear and causal system, the domains being interrelated through the Fourier transform. The time domain is attractive in that the whole transient can be recorded in a single measurement. Hence, there are devices in commercial use that record spectra in the time domain by measuring the voltage transient at a number of instances after the current pulse has been switched off. The primary current signal in these devices is generally a pulse train composed of pulses of finite duration. The pulse train has advantages over the single pulse because it permits the measurements to be repeated and thus improves the signal‐to‐noise (S/N) ratio of the measurements.

scholarly journals Adaptive complementary ensemble EMD and energy-frequency spectra of cryptocurrency prices

2021 ◽  
pp. 2141008
Author(s):  
Tim Leung ◽  
Theodore Zhao
Keyword(s):  
Time Series ◽  
Spectral Analysis ◽  
Ensemble Empirical Mode Decomposition ◽  
Intrinsic Mode Functions ◽  
Original Time Series ◽  
Frequency Spectra ◽  
Mode Decomposition ◽  
Original Time ◽  
Instantaneous Frequencies ◽  
Instantaneous Energy

In this study, we study the price dynamics of cryptocurrencies using adaptive complementary ensemble empirical mode decomposition (ACE-EMD) and Hilbert spectral analysis. This is a multiscale noise-assisted approach that decomposes any time series into a number of intrinsic mode functions, along with the corresponding instantaneous amplitudes and instantaneous frequencies. The decomposition is adaptive to the time-varying volatility of each cryptocurrency price evolution. Different combinations of modes allow us to reconstruct the time series using components of different timescales. We then apply Hilbert spectral analysis to define and compute the instantaneous energy-frequency spectrum of each cryptocurrency to illustrate the properties of various timescales embedded in the original time series.

Heart Rate Variability, Emotions, and Music

2010 ◽  
Vol 24 (2) ◽  
pp. 112-119 ◽  
Author(s):  
F. Riganello ◽  
A. Candelieri ◽  
M. Quintieri ◽  
G. Dolce
Keyword(s):  
Data Mining ◽  
Heart Rate ◽  
Heart Rate Variability ◽  
Vegetative State ◽  
Low Frequency ◽  
Emotional Reactions ◽  
Heart Beat ◽  
Healthy Controls ◽  
Frequency Spectra ◽  
Emotional Value

The purpose of the study was to identify significant changes in heart rate variability (an emerging descriptor of emotional conditions; HRV) concomitant to complex auditory stimuli with emotional value (music). In healthy controls, traumatic brain injured (TBI) patients, and subjects in the vegetative state (VS) the heart beat was continuously recorded while the subjects were passively listening to each of four music samples of different authorship. The heart rate (parametric and nonparametric) frequency spectra were computed and the spectra descriptors were processed by data-mining procedures. Data-mining sorted the nu_lf (normalized parameter unit of the spectrum low frequency range) as the significant descriptor by which the healthy controls, TBI patients, and VS subjects’ HRV responses to music could be clustered in classes matching those defined by the controls and TBI patients’ subjective reports. These findings promote the potential for HRV to reflect complex emotional stimuli and suggest that residual emotional reactions continue to occur in VS. HRV descriptors and data-mining appear applicable in brain function research in the absence of consciousness.

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