The zero attraction affine projection algorithm (ZA-APA) achieves better performance in terms of convergence rate and steady state error than standard APA when the system is sparse. It uses l1 norm penalty to exploit sparsity of the channel. The performance of ZA-APA depends on the value of zero attractor controller. Moreover a fixed attractor controller is not suitable for varying sparsity environment. This paper proposes an optimal adaptive zero attractor controller based on Mean Square Deviation (MSD) error to work in variable sparsity environment. Experiments were conducted to prove the suitability of the proposed algorithm for identification of unknown variable sparse system.

With the extinction of fossil fuels and high increase in power demand, the necessity for renewable energy power generation has increased globally. Solar PV is one such renewable energy power generation, widely used these days in the power sector. The inverters used for power conversion suffer from power losses in the switching elements. This paper aims at the detailed analysis on switching losses in these inverters and also aims at increasing the efficiency of the inverter by reducing losses. Losses in these power electronic switches vary with their types. In this analysis the most widely used semiconductor switches like the insulated gate bipolar transistor (IGBT) and metal oxide semiconductor field effect transistor (MOSFET) are compared. Also using the sinusoidal pulse width modulation (SPWM) technique, improves the system efficiency considerably. Two SPWM-based singlephase inverters with the IGBT and MOSFET are designed and simulated in a MATLAB Simulink environment. The voltage drop and, thereby, the power loss across the switches are compared and analysed. The proposed technique shows that the SPWM inverter with the IGBT has lower power loss than the SPWM inverter with the MOSFET.