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A key problem at hardware implementation of artificial neural networks based on memristors (ANNM) is to ensure the required accuracy of their operation at the transition from models to real fabricated memristive devices. Due to a number of factors, such as the imperfections in state-of-theart memristors and memristive arrays, ANNM design and tuning methods, additional computation errors occur during the process of ANNM hardware implementation. This article proposes a general approach to the simulation and design of a multilayer perceptron (MLP) network on the basis of cross-bar arrays of metal-oxide memristive devices. The proposed approach uses the ANNM theory, tolerance theory, simulation methodology and experiment design. The tolerances analysis and synthesis process is performed for the ANNM hardware implementation on the basis of two arrays of memristive microdevices in the original 16×16 cross-bar topology being a component of bidirectional adaptive neural interface for automatic registration and stimulation of bioelectrical activity of a living neuronal culture used in robotics control system. The ANNM is trained for solving a nonlinear classification problem of stable information characteristics registered in the culture grown on a multi-electrode array. Memristive devices are fabricated on the basis of a newly engineered Au/Ta/ZrO 2 (Y)/Ta 2 O 5 /TiN/Ti multilayer structure, which contains self-organized interface oxide layers, nanocrystals and is specially developed to obtain robust resistive switching with low variation of parameters. An array of memristive devices is mounted into a standard metalceramic package and can be easily integrated into the neurointerface circuit. Memristive devices demonstrate bipolar switching of anionic type between the high-resistance state and low-resistance state and can be programmed to set the intermediate resistive states with a desired accuracy. The ANNM tuning, testing and control are implemented by the FPGA-based control subsystem. All developed models and algorithms are implemented as Python-based software.

The paper proves the necessity of revising the methodology of housing and communal services pricing in connection with the implementation of the city development concept within the framework of the green agenda and the strategies and programs development aimed at ecologically important problems resolution, clean technologies development, natural resource conservation, and the increase in the population living standards as well. It is shown that the creation of ecologically sustainable urban systems requires not only the development and implementation of innovative technologies and attraction of financial resources but also the assessment of their consequences, such as changes in the volumes of consumed housing and communal services and tariffs for them. Adjustments to the methodology of housing and communal services pricing should ensure the process of providing quality services at affordable prices for consumers. The main results of the study demonstrate that modern cities should utilize innovative solutions aimed at changing the approach to operating and managing housing and communal services to meet the requirements of ecological safety and sustainability. Implementing the recommendations to improve the ecological situation and sustainability of housing and communal services can become a key factor in creating a peaceful, successful, and efficient urban environment.