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This lecture covers statistical signal processing tools for wireless communications, focusing on topics such as spectral estimation, signal detection, classification, and adaptive filtering. Students will learn to model wireless communication signals, perform spectral analysis, and work on mini-projects to implement and compare tools. The course emphasizes practical applications in wireless systems and provides hands-on experience with Python or Matlab. The lecture also explores advanced tools beyond the basics, encouraging students to innovate and improve existing solutions. Evaluation is based on problem-solving quality, implementation, innovation, and presentation skills.