The paper presents an analysis of third-generation spiking neural networks application to solving regression tasks. It considers the main models of spiking neurons (LIF, Izhikevich, Hodgkin-Huxley) from the perspective of their computational complexity and suitability for regression problems. Methods for encoding real-valued data into spike sequences are analyzed: rate coding, temporal coding, and population coding. Special attention is given to methods of decoding output spikes into continuous values, including rate decoding, first spike timing decoding, membrane potential decoding, and population voting. An assessment of the energy efficiency of various approaches is conducted, demonstrating a 100-200 fold reduction in energy consumption compared to traditional neural networks while maintaining acceptable accuracy. The research results confirm the promising application of spiking networks in embedded systems and Internet of Things devices.
Keywords: spiking neural networks, spike neuron model, spike coding, regression, energy efficiency
The paper presents an integrated approach using machine learning methods for choosing a trading strategy on the currency exchange. The presented approach uses the calculation of the linear regression angle coefficient by log return indicators and determination of the BTC/USD currency pair quotes trend in the next period based on the calculated coefficient sign. The feedforward multilayer neural network is used to predict the angle coefficient value in the next ten minute period for the current twenty minute period. The paper proposes a combined approach to the use of machine learning methods for choosing a trading strategy in foreign exchange. The study presents the results of experiments evaluating the practical results of effective and ineffective strategies based on the predicted values of linear regression coefficients.
Keywords: diversification of management, production diversification, financial and economic purposes of a diversification, technological purposes of ensuring flexibility of production