Building a noise-tolerant code based on a holographic representation of arbi-trary digital information

Timofeev, Alexander; Sultanov, Albert Kh.

doi:10.18287/2412-6179-co-739

Cited by 5 publications

(4 citation statements)

References 8 publications

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“…In this way, electronic information that meets the user's input conditions is retrieved from the database and returned to the user according to the matching degree. is electronic information usually involves a wide range of types, and most of them do not match the user's search target, resulting in low search efficiency [8]. Parmar and Pateria expressed that there is an urgent need for an efficient and accurate automatic electronic information classification system to complete the classification of electronic information [9].…”

Section: Literature Reviewmentioning

confidence: 99%

Research on Electronic Information Feature Extraction and Classification Recognition Algorithm Based on Deep Learning

2022

Security and Communication Networks

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In order to make up for the shortcomings of traditional electronic information characteristics and classification recognition algorithms and improve the application ability of the technology, a special extraction algorithm based on the performance of deep multilayer autoencoders is required, and the training of deep learning network model is not supervised with pretraining and the supervision of the margin-based Fisher guidelines. The regularization means in the process of data generating pretraining and carving will prevent the prefining training. Experimental results on multiple data distributions further determine the efficiency of the algorithm. By analyzing the depth learning model, the image information in electronic information is used as an example, and its extraction technology is discussed, and the direction is indicated further. The experimental results show that the acceptance performance of the DMFA algorithm is improved in some cases compared with similar algorithms. And in Ionosphere, PIMA, IRIS Data Set this algorithm acquires the improvement effect, but the results obtained in other data sets are not ideal, thereby obtaining the most use of electronic information feature extraction and classification recognition.

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Section: Literature Reviewmentioning

confidence: 99%

Research on Electronic Information Feature Extraction and Classification Recognition Algorithm Based on Deep Learning

2022

Security and Communication Networks

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“…Therefore, at the first stage of the study of this technology, a rational solution is to reduce the amount of transmitted information and use the simplest images for encoding messagesone-bit matrices of the original object, for example, 16x16. When using a positional code, as, for example, in holographic coding 14,15 , the hologram of the simplest object (one luminous point) is an image of a Fresnel zone plate. In this case, the useful amount of transmitted information is 8 bits (the coordinates of the luminous point on the image of the object sized 16x16, corresponding to the coordinates of the center of the Fresnel zones on the hologram).…”

Section: Statement Of the Problemmentioning

confidence: 99%

“…The receiver calculates the spectrum of the received signal. The digital array representing the spectrum is considered as a one-dimensional hologram of the original digital block and is decoded by the holographic method described in 15 the original data block is restored from the digital hologram.…”

Section: Solution Optionsmentioning

confidence: 99%

Usage of holography for parallel transmission of information

Timofeev,

Sultanov,

Meshkov

et al. 2023

Optical Technologies for Telecommunications 2022

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The article discusses the possibilities of using holography for parallel transmission of information in communication channels. Existing channels use serial transmission. At the same time, there is an effect that can be considered as a parallel transmission of information – holography. To transmit a hologram over a communication channel, it is necessary to transpose the space-time matrix. In this case, the information is deployed in space, and two local points are used in time – the moment of the formation of the object and the moment of the formation of the hologram. One option is optical holography, where an array of lasers pointed at the receiver matrix forms an interference pattern on it. The second option is the use of radio holography, the third is the transfer of the communication channel from the space-time domain to the time-frequency domain. To do this, one can use the transfer of the information block into a linear array of the spectrum in the frequency domain (time-frequency transposition). In this case, the hologram is aligned in the frequency space – the shape of the hologram corresponding to the transmitted information block contains the signal spectrum. The approaches considered are a problem statement for developing methods for parallel holographic transmission and creating communication channels that practically do not have an upper bandwidth limit. The theoretical limit is the transmission rate of a hologram – the amount of information contained in a three-dimensional image of a complex object, within the duration of one period of an electromagnetic wave.

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“…Достаточно широкой областью обработки изображений является цифровая голография. Применение цифровой голографии открывает широкие возможности для качественного и, более того, точного количественного анализа свойств объекта, таких как смещение точек поверхности при анализе деформаций, определение формы объекта, измерение коэффициента преломления в прозрачных средах, изучение траекторий частиц, микроскопия, радиоголография, помехоустойчивое кодирование и многое другое [3][4][5][6][7][8][9][10][11]. В упомянутых случаях изменение состояния изучаемого объекта приводит к изменению объектной волны и получаемой интерференционной картины, которая записывается цифровым образом.…”

Section: обработка информации и управлениеunclassified

Influence of noise and sampling rate on the discrete image representation error

Timofeev

Sultanov

2021

ICS

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Introduction: Digital registration of images is accompanied not only by an error caused by finite spatial resolution of the photo matrix, but also by the effect of noise whose contribution to the total error decreases with an increase in the aperture of the photosensors in the matrix. Thus, changing the sampling rate has the opposite effect on the sampling error and on the error caused by the noise. Purpose: Finding the optimal image sampling rate which would provide the minimum sampling error in the presence of noise. Results: We have studied how an image discrete representation error depends on the sampling frequency and noise level. The image sampling process in the presence of noise was simulated in the MATLAB environment. The dependencies of the root-mean-square deviation of the sampling error caused by spectrum truncation (decrease in the passband of the low-pass filter) and the noise component of the error on the sampling frequency were plotted. A theorem is formulated on the upper bound of the sampling theorem: when sampling a function of finite duration in the presence of noise, there is a finite minimum value of the sampling error which is determined by the shape of the spectrum of the function and the noise level. Practical relevance: It is advisable to use the research results when choosing a photomatrix by the number of pixels for recording images in the presence of noise, as well as when choosing a low-pass filter passband for primary processing of a digital image.

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Building a noise-tolerant code based on a holographic representation of arbi-trary digital information

Cited by 5 publications

References 8 publications

Research on Electronic Information Feature Extraction and Classification Recognition Algorithm Based on Deep Learning

Research on Electronic Information Feature Extraction and Classification Recognition Algorithm Based on Deep Learning

Usage of holography for parallel transmission of information

Influence of noise and sampling rate on the discrete image representation error

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