Lecture

Wireless Receivers: Parameter Estimation

Related lectures (86)
Signal Processing: Sampling and Reconstruction
Covers the concepts of quantization, coding, and sampling in signal processing.
Discrete Fourier Transform: Sampling and Interpretation
Explores discrete Fourier transform, signal reconstruction, sampling interpretation, and periodic signal repetition.
Signal Processing: Sampling and Reconstruction
Covers Fourier transform, sampling, reconstruction, Nyquist frequency, and ideal signal reconstruction.
Wireless Receivers: OFDM
Covers the fundamentals of Orthogonal Frequency Division Multiplexing (OFDM) in wireless communication systems.
Optimization of Neuroprosthetic Systems
Explores the optimization of neuroprosthetic systems, including sensory feedback restoration and neural stimulation strategies.
Parametric Signal Models: Matlab Practice
Covers parametric signal models and practical Matlab applications for Markov chains and AutoRegressive processes.
Fourier Transform: Basics and Applications
Covers the basics of the Fourier transform and its applications in signal processing.
Sampling and Reconstruction
Covers sampling, Fourier Transform, and reconstruction using low-pass filters in signal processing.
Signals, Instruments, and Systems
Explores signals, instruments, and systems, covering ADC, Fourier Transform, sampling, signal reconstruction, aliasing, and anti-alias filters.
Frequency Estimation (Theory)
Covers the theory of numerical methods for frequency estimation on deterministic signals, including Fourier series and transform, Discrete Fourier transform, and the Sampling theorem.

Graph Chatbot

Chat with Graph Search

Ask any question about EPFL courses, lectures, exercises, research, news, etc. or try the example questions below.

DISCLAIMER: The Graph Chatbot is not programmed to provide explicit or categorical answers to your questions. Rather, it transforms your questions into API requests that are distributed across the various IT services officially administered by EPFL. Its purpose is solely to collect and recommend relevant references to content that you can explore to help you answer your questions.