Related lectures (35)
Signals & Systems II: Z Transform Properties and Inversion
Explores Z transform properties, ROC, inversion, and signal support behavior.
Data Preprocessing: Handling Challenges
Delves into advanced data preprocessing techniques, covering categorical encoding, missing data handling, and unbalanced datasets, emphasizing performance metrics and classifier comparison.
Smart Sensors for the IoT: ADCs Fundamentals
Explores ADCs fundamentals for IoT smart sensors, covering quantization, non-idealities, and topologies.
Analog to Digital Conversion
Explores analog to digital conversion principles, CMOS technology, precision limitations, and integration of converters.
Wireless Receivers: Time and Phase Offset Compensation
Covers the impact of time and phase offset in wireless receivers and discusses compensation techniques.
Model Assessment: Metrics and Selection
Explores model assessment metrics, selection techniques, bias-variance tradeoff, and handling skewed data distributions in machine learning.
Data Representations and Processing
Covers data representations, challenges of imbalanced data, and strategies for data normalization and cleaning.
Transition to/from Continuous Time Signals and Passband Modulation
Explores the transition between continuous time signals and passband modulation techniques.
The Sampling Theorem
Covers the sampling theorem, impulse train sampling, bandlimited signals, and the Nyquist rate.
Nyquist Rate and Sampling Theorem
Explains the Nyquist rate and Sampling Theorem for reconstructing band-limited signals through examples and sampling techniques.

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