FREQUENCY-SPATIAL TRANSFORMATION: A PROPOSAL FOR PARSIMONIOUS INTRA-CORTICAL COMMUNICATION

1996 ◽  
Vol 07 (05) ◽  
pp. 591-598
Author(s):  
REGEV LEVI ◽  
EYTAN RUPPIN ◽  
YOSSI MATIAS ◽  
JAMES A. REGGIA
Keyword(s):  
Neural Network ◽  
Input Signal ◽  
Cortical Neurons ◽  
External Input ◽  
Resonant Peak ◽  
Signal Frequency ◽  
Spatial Transformation ◽  
Input Signal Frequency ◽  
Mexican Hat ◽  
Impedance Magnitude

This work examines a neural network model of a cortical module, where neurons are organized on a 2-dimensional sheet and are connected with higher probability to their spatial neighbors. Motivated by recent findings that cortical neurons have a resonant peak in their impedance magnitude function, we present a frequency-spatial transformation scheme that is schematically described as follows: An external input signal, applied to a small input subset of the neurons, spreads along the network. Due to a stochastic component in the dynamics of the neurons, the frequency of the spreading signal decreases as it propagates through the network. Depending on the input signal frequency, different neural assemblies will hence fire at their specific resonance frequency. We show analytically that the resulting frequency-spatial transformation is well-formed; an injective, fixed, mapping is obtained. Extensive numerical simulations demonstrate that a homogeneous, well-formed transformation may also be obtained in neural networks with cortical-like “Mexican-hat” connectivity. We hypothesize that a frequency-spatial transformation may serve as a basis for parsimonious cortical communication.

scholarly journals Reducing the Impact of the Frequency Change on the Formation of Orthogonal Components of the Relay Protection Input Signals

2020 ◽  
Vol 63 (1) ◽  
pp. 42-54 ◽  
Author(s):  
E. A. Romaniuk ◽  
V. Yu. Rumiantsev ◽  
Yu. V. Rumiantsev ◽  
A. A. Dziaruhina
Keyword(s):  
Fourier Transform ◽  
Discrete Fourier Transform ◽  
Digital Filter ◽  
Input Signal ◽  
Digital Filters ◽  
Signal Frequency ◽  
Filter Model ◽  
Input Signal Frequency ◽  
Orthogonal Components ◽  
The Impact

Digital filters made with the use of discrete Fourier Transform are applied in most microprocessor protections produced both in the home country and abroad. When the input signal frequency deviates from the value to which these filters are configured, a signal is generated at their output with oscillation amplitude that is proportional to the deviation of the signal frequency from the specified one. The article proposes an algorithm for compensating the oscillations of orthogonal components of the output signals of digital filters implemented on the basis of a discrete Fourier transform, when the input signal frequency deviates from the nominal one. A mathematical model of the proposed digital filter with an algorithm for compensating the oscillations of its orthogonal components, as well as a signal model for reproducing input effects, is implemented in the MatLab-Simulink dynamic modeling environment. The digital filter model is provided with two channels, viz. a current channel and a voltage channel, which makes it possible to simulate their operation in relation to protections that use one or two input values, for example, for current and remote protection. Verification of the functioning of the digital filter model with compensation for fluctuations in its output signal was carried out with the use of two types of test effects, viz. a sinusoidal signal with a frequency of 48–51 Hz (idealized effect), and the effects that are close to the real secondary signals of measuring current transformers and voltage transformers in case of short circuits accompanied by a decrease in frequency. The conducted computational experiments with deviation of frequency from the nominal one, revealed the presence of undamped oscillations at the output of standard digital Fourier filters and their almost complete absence in the proposed digital filters. This makes us possible to recommend digital filters based on a discrete Fourier transform supplemented by an algorithm for compensation of fluctuations in the amplitudes of the output signals for the use in microprocessor protection.

scholarly journals Basic Characteristics of IEC Flickermeter Processing

2012 ◽  
Vol 2012 ◽  
pp. 1-9 ◽  
Author(s):  
Jarosław Majchrzak ◽  
Grzegorz Wiczyński
Keyword(s):  
Input Signal ◽  
Standard Test ◽  
Signal Frequency ◽  
Signal Source ◽  
Short Term ◽  
Voltage Fluctuations ◽  
Input Signal Frequency ◽  
A Value ◽  
Bandwidth Limitation ◽  
Basic Characteristics

Flickermeter is a common name for a system that measures the obnoxiousness of flicker caused by voltage fluctuations. The output of flickermeter is a value of short-term flicker severity indicator, . This paper presents the results of the numerical simulations that reconstruct the processing of flickermeter in frequency domain. With the use of standard test signals, the characteristics of flickermeter were determined for the case of amplitude modulation of input signal, frequency modulation of input signal, and for input signal with interharmonic component. For the needs of simulative research, elements of standard IEC flickermeter signal chain as well as test signal source and tools for acquisition, archiving, and presentation of the obtained results were modeled. The results were presented with a set of charts, and the specific fragments of the charts were pointed out and commented on. Some examples of the influence of input signal’s bandwidth limitation on the flickermeter measurement result were presented for the case of AM and FM modulation. In addition, the diagrams that enable the evaluation of flickermeter’s linearity were also presented.

Influence of Alternating Current Frequency on Output Voltage at Electromagnetic Method of Metal Control

2019 ◽  
Vol 945 ◽  
pp. 879-884
Author(s):  
I.R. Kuzeev ◽  
A.S. Valiev ◽  
V.Yu. Pivovarov
Keyword(s):  
Input Signal ◽  
Life Assessment ◽  
Signal Frequency ◽  
Electric Signal ◽  
Continuous Control ◽  
Input Signal Frequency ◽  
Electromagnetic Processes ◽  
Function Graph ◽  
Sinusoidal Function

The equipment of oil refineries and other hazardous production facilities operate under high pressures and temperatures. Such operation conditions require continuous control and equipment remaining operation life period assessment. The existing methods of diagnostics are based on probabilistic remaining life assessment and use data regarding wall thickness variation during the operation process. The present article presents the method of accumulated damage assessment and its approximation to the limiting state, based on electromagnetic processes studying by means of eddy current control method. The main purpose of studies was determination of optimal value of input signal frequency, which could the most informative for determination of regularity of electric signal parameters change depending on the level of accumulated damages. Steel grade 09Г2С samples were used as the subject of studies. The samples were exposed to static tension under constant rate and during the process of samples deformation we measured the value of electric signal under three frequencies: 100 Hz, 10 kHz, and 1 MHz Based on the obtained results we prepared output signal voltage-relative elongation dependencies, which showed that accumulation of plastic deformations in metal leads to reduction of signal amplitude. Particularly interesting was dependence under 1 MHz frequency, under which electromagnetic processes occur in subsurface and surface layers. This dependence was of some regular nature, which was described by means of the sinusoidal function. Graph of the obtained function qualitatively describes the experimental dependence. On the basis of obtained results we can make a conclusion that optimal input signal frequency is within megahertz range, under which difference between the sinusoidal function graph and the empirical curve is minimum.

scholarly journals Understanding the Input Signal Frequency Effects on the Resistive Window of Memristors

2020 ◽  
Author(s):  
Marcos Maestro Izquierdo ◽  
Mireia B. Gonzalez ◽  
Francesca campabadal ◽  
Enrique Miranda ◽  
Jordi Suñé
Keyword(s):  
Input Signal ◽  
Signal Amplitude ◽  
Electrical Stimulus ◽  
Balance Model ◽  
Signal Frequency ◽  
Electrical Behavior ◽  
Memory State ◽  
Input Signal Frequency ◽  
Input Signal Amplitude ◽  
The Difference

As theoretically predicted by Prof. Chua, the input signal frequency has a major impact on the electrical behavior of memristors. According with one of the so-called fingerprints of such devices, the resistive window, <i>i.e.</i> the difference between the low and high resistance states, shrinks as the frequency increases for a given input signal amplitude. Physically, this effect stems from the incapability of ions/vacancies to follow the external electrical stimulus. In terms of the electrical behavior, the collapse of the resistive window can be ascribed to the shift of the set/reset voltages toward higher values. Moreover, for a given frequency, the resistance window increases with the signal amplitude. In this letter, we show that both phenomena are the two sides of the same coin and that can be consistently explained after considering the snapback effect and a balance model equation for the device memory state.

Muscle Tuning During Running: Implications of an Un-tuned Landing

2006 ◽  
Vol 128 (6) ◽  
pp. 815-822 ◽  
Author(s):  
Katherine A. Boyer ◽  
Benno M. Nigg
Keyword(s):  
Soft Tissue ◽  
Resonance Frequency ◽  
Input Signal ◽  
The Body ◽  
Signal Frequency ◽  
Tissue Compartment ◽  
Input Signal Frequency ◽  
Input Signals ◽  
Tissue Compartments ◽  
The Impact

Background: The impact force in heel-toe running is an input signal into the body that initiates vibrations of the soft tissue compartments of the leg. These vibrations are heavily damped and the paradigm of muscle tuning suggests the body adapts to different input signals to minimize these vibrations. The objectives of the present study were to investigate the implications of not tuning a muscle properly for a landing with a frequency close to the resonance frequency of a soft tissue compartment and to look at the effect of an unexpected surface change on the subsequent step of running. Method: Thirteen male runners were recruited and performed heel-toe running over two surface conditions. The peak accelerations and biodynamic responses of the soft tissue compartments of the leg along with the EMG activity of related muscles were determined for expected soft, unexpected hard and expected hard landings. Results and Conclusions: For the unexpected hard landing there was a change in the input frequency of the impact force, shifting it closer to the resonance frequency of the soft tissue compartments. For the unexpected landing there was no muscle adaptation, as subjects did not know the running surface was going to change. In support of the muscle-tuning concept an increase in the soft tissue acceleration did occur. This increase was greater when the proximity of the input signal frequency was closer to the resonance frequency of the soft tissue compartment. Following the unexpected change in the input signal a change in pre-contact muscle activity to minimize soft tissue compartment vibrations was not found. This suggests if muscle tuning does occur it is not a continuous feedback response that occurs with every small change in the landing surface properties. In previous studies with significant adaptation periods to new input signals significant correlations between the changes in the input signal frequency and the EMG intensity have been shown, however, changes in soft tissue accelerations have not been found. The results of the present study showed that changes in these soft tissue accelerations can occur in response to a resonance frequency input signal when a muscle reaction has not happened.

scholarly journals Understanding the Input Signal Frequency Effects on the Resistive Window of Memristors

2020 ◽  
Author(s):  
Marcos Maestro Izquierdo ◽  
Mireia B. Gonzalez ◽  
Francesca campabadal ◽  
Enrique Miranda ◽  
Jordi Suñé
Keyword(s):  
Input Signal ◽  
Signal Amplitude ◽  
Electrical Stimulus ◽  
Balance Model ◽  
Signal Frequency ◽  
Electrical Behavior ◽  
Memory State ◽  
Input Signal Frequency ◽  
Input Signal Amplitude ◽  
The Difference

As theoretically predicted by Prof. Chua, the input signal frequency has a major impact on the electrical behavior of memristors. According with one of the so-called fingerprints of such devices, the resistive window, <i>i.e.</i> the difference between the low and high resistance states, shrinks as the frequency increases for a given input signal amplitude. Physically, this effect stems from the incapability of ions/vacancies to follow the external electrical stimulus. In terms of the electrical behavior, the collapse of the resistive window can be ascribed to the shift of the set/reset voltages toward higher values. Moreover, for a given frequency, the resistance window increases with the signal amplitude. In this letter, we show that both phenomena are the two sides of the same coin and that can be consistently explained after considering the snapback effect and a balance model equation for the device memory state.

A Sigma-Delta Modulator System Design with 2-2 Mash Structure

2014 ◽  
Vol 981 ◽  
pp. 121-124
Author(s):  
Yang Yang ◽  
Guo Dong Sun ◽  
Ming Xin Song ◽  
Zhi Ming Wang
Keyword(s):  
System Design ◽  
Input Signal ◽  
Electronic Equipment ◽  
Signal Frequency ◽  
Behavior Model ◽  
Sigma Delta Modulator ◽  
Sigma Delta ◽  
Design Efficiency ◽  
Input Signal Frequency ◽  
Modulator Structure

Σ-Δ modulator structure is increasingly becoming complex, it is very necessary to improve the design efficiency by the level of behavior model in the simulation. The paper discussed several important Σ-Δ modulators with ideal factors, and gives corresponding behavior model. Then, the paper shows a behavior level design with non-ideal factors. Under the condition that sample rate is 256 and input signal frequency is 250 KHz, the SNR can get 105 dB, the effective bit can get 16 bit. It can be used in audio and electronic equipment.

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