In recent years, Multiple Input- Multiple Output (MIMO) has been used to expand data transfer for ensuring consistency. The transmitter and receiver use several antennas and they can achieve high spectral characteristics. However, as the numbers of users and antennas increase rapidly, the complexity of the system increases and it becomes a major problem in many detection systems. It is important to develop sophisticated components to improve compliance with many standards without compromising Bit Error Rate (BER) performance of the components. The proposed work introduces a New Hybrid MIMO Detector (NHMD), which provides the solution for the complicated design procedure. In this proposed method an Optimal Differential Evolution (ODE) algorithm has been designed to select multiple detection detectors. In addition, this method uses a parallel processing to reduce the amount of arithmetic logic. The proposed NHMD method is implemented for cylindrical devices belonging to different FPGA families with different antenna configurations (2 × 2, 4 × 4). The proposed NHMD method provides superior quality by combining multiple detectors. The simulation results confirm that the NHMD method uses low equipment as well as low power consumption and provides high efficiency without affecting BER performance.

Purpose The brushless direct current motor (BLDCM) is widely accepted and adopted by many industries instead of direct current motors due to high reliability during operation. Brushless direct current (BLDC) has outstanding efficiency as losses that arise out of voltage drops at brushes and friction losses are eliminated. The main factor that affects the performance is temperature introduced in the internal copper core windings. The control of motor speed generates high temperature in BLDC operation. The high temperature is due to presence of ripples in the operational current. The purpose is to present an effective controlling mechanism for speed management and to improve the performance of BLDCM to activate effective management of speed. Design/methodology/approach The purpose is to present an optimal algorithm based on modified moth-flame optimization algorithm over recurrent neural network (MMFO-RNN) for speed management to improve the performance. The core objective of the presented work is to achieve improvement in performance without affecting the design of the system with no additional circuitry. The management of speed in BLDCM has been achieved through reduction or minimization of ripples encircled with torque of the motor. The implementation ends in two stages, namely, controlling the loop of torque and controlling the loop of speed. The MMFO-RNN starts with error optimization, which arises from both the loops, and most effective values have been achieved through MMFO-RNN protocol. Findings The parameters are enriched with Multi Resolution Proportional Integral and Derivative (MRPID) controller operation to achieve minimal ripples for the torque of BLDC and manage the speed of the motor. The performance is increased by adopting this technique approximately 12% in comparison with the existing methodology, which is the main contributions of the presented work. The outcomes are analyzed with the existing methodologies through MATLAB Simulink tool, and the comparative analyses suggest that better performance of the proposed system produces over existing techniques, and proto type model is developed and cross verifies the proposed system. Originality/value The MMFO-RNN starts with error optimization, which arises from both the loops, and most effective values have been achieved through MMFO-RNN protocol. The parameters are enriched with MRPID controller operation to achieve nil or minimal ripples and to encircle the torque of Brushless Direct Current and manage the speed.

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