A Memristor Model with a Modified Window Function and Activation Thresholds

Mladenov, Valeri; Kirilov, Stoyan

doi:10.1109/iscas.2018.8351429

Cited by 21 publications

(117 citation statements)

References 16 publications

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“…The window function used in this research is described in detail in [17]. The memristor model used for the simulations in the present research is described in details in [15,16].…”

Section: A Description Of the Used Memristor Model And Its Fine Tuninmentioning

confidence: 99%

“…The memristor model used for the simulations in the present research is described in details in [15,16]. The modified window function f M (x) proposed in [17] is based both on Joglekar [5] and Biolek [6] window functions. It is a plain linear combination of these window functions.…”

Section: A Description Of the Used Memristor Model And Its Fine Tuninmentioning

confidence: 99%

“…The motivation for the present research is to fill this absence, proposing additional and detailed research of a fragment of a hybrid memory circuit, containing all the elements sufficient for the basic writing and reading processes: word lines, bit lines, write enable and read enable lines, four memristor elements, and four isolating MOS transistors [13]. For this investigation, a highly nonlinear drift model [10,15,16] and a modified nonlinear window function, proposed by the author in [17] will be used. A comparison to experimental data [10] will also be realized.…”

Section: Introductionmentioning

confidence: 99%

“…A comparison to experimental data [10] will also be realized. The ability of the applied memristor model [10,16], together with the modified window function [17], for realistic representation of the performance of complex memristor devices for soft-and hard-switching will be established. For soft-switching mode the state variable does not reach its boundary values while for hard-switching the state variable reaches its limiting borders.…”

Section: Introductionmentioning

confidence: 99%

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Analysis and Simulations of Hybrid Memory Scheme Based on Memristors

Mladenov

2018

Electronics

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The investigation of new memory schemes is significant for future generations of electronic devices. The purpose of this research is to present a detailed analysis of the processes in the memory elements of a memory section with memristors and isolating Metal Oxide Semiconductor (MOS) transistors. For the present analysis, a modified window function previously proposed by the author in another memristor model is used. The applied model is based on physical nonlinear current-voltage and state-voltage characteristics. It is suitable for illustration of the processes in the memristors for both writing and reading procedures. The memory scheme is simulated using a nonlinear drift model with an improved window function. The used model was previously adjusted according to the reference Pickett model. The memory circuit is analyzed for writing and reading information procedures. The memristor current-voltage relationship is compared to physical experimental characteristics and to results acquired by the use of basic window functions. A satisfactory coincidence between the corresponding results is established. For the used logical signals, the memory elements operate in a state near to hard-switching mode. It is confirmed that the memristor model with a modified window function applied here is suitable for investigating complex memristor circuits for a general operating mode.

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“…The window function used in this research is described in detail in [17]. The memristor model used for the simulations in the present research is described in details in [15,16].…”

Section: A Description Of the Used Memristor Model And Its Fine Tuninmentioning

confidence: 99%

Section: A Description Of the Used Memristor Model And Its Fine Tuninmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Analysis and Simulations of Hybrid Memory Scheme Based on Memristors

Mladenov

2018

Electronics

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“…Chaotic behavior appears in a variety of analog systems, including circuits with memristive elements [8,9], elements with hysteresis [10], and other nonlinear devices [11] (e.g., ones with exponential nonlinearity [12]), as well as in analog artificial neural networks, chaotic sensing, and transmitting systems. The analog electrical oscillators demonstrate 'real' chaos, representing dynamics close to continuous mathematical models.…”

Section: Introductionmentioning

confidence: 99%

Accurate Synchronization of Digital and Analog Chaotic Systems by Parameters Re-Identification

et al. 2018

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The verification of the digital models of chaotic systems and processes is a valuable problem in many practical applications, such as nonlinear control and communications. In our study, we propose a hybrid technique for chaotic systems' identification, based on the chaotic synchronization of digital and analog counterparts and a numerical optimization method used for the fine tuning of parameters. An analog circuit implementing the Rössler oscillator with digitally controlled parameters was chosen as an identification object, and the FPGA model was used as a digital counterpart for coupling and parameter retrieval. The synchronization between analog and digital chaotic models can be used to estimate the quality of an identification procedure. The results of this study clarify the practical bounds of digital and analog systems' equivalence. They also contribute to the problem of designing technical systems possessing advantages of both analog and digital chaotic generators (e.g., a high accuracy and protection from quasi-chaotic oscillation modes).

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