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Signal processing can be found in many applications and its primary goal is to provide underlying information for the purpose of decision making. However, most of the real-world signals are challenging in nature as they are nonstationary, i.e., their statistics are time variant. Therefore, time or frequency descriptions, alone, are insufficient to provide comprehensive information about these challenging signals. On the contrary, extracting joint time-varying frequency characteristics of signals has an immense potential for revealing the nonstationary behaviour of signals better. This book is...