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Lecture
Digital Filters: Structure and Implementation
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Related lectures (44)
AmpliOp Response and Filter Design
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Covers the design of active filters based on operational amplifiers and impedance analysis.
Sampling: Signal Reconstruction and Aliasing
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Covers the importance of sampling, signal reconstruction, and aliasing in digital representation.
Digital Filters Synthesis: Bilinear Transformation and Frequency Response
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Explores the synthesis of digital filters from analog filters using the bilinear transformation method and Chebyshev's criterion.
Digital Filters: RII Filters - Part 2
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Explores RII filters, analog-to-digital filter conversion, stability, and filter construction.
Frequency Domain Analysis
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Explores system analysis in the frequency domain, covering sinusoidal transfer functions, resonant frequencies, and filter design.
Convolutional Neural Networks
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Covers convolutional neural networks, filter operations, and their applications in signal processing and image analysis.
Signals, Instruments, and Systems: System Properties and Transforms
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Introduces system properties, Laplace Transform, and analog filters for signal analysis.
Switched-Capacitor Filters: Design and Synthesis
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Covers the design and synthesis of switched-capacitor filters focusing on cascade and ladder filter designs.
Smart Sensors for the IoT: ADCs Fundamentals
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Explores ADCs fundamentals for IoT smart sensors, covering quantization, non-idealities, and topologies.
Filter Structures: Part 2
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Explores the geometric interpretation of filter responses and the challenges of achieving causal filters in real-time signal processing.
Digital Filters: Phase Response and Stability
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Explores phase response constraints, minimum phase systems, and digital filter design.
Feedback and Stability: Active Filters
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Explores feedback, stability, and active filters, covering various amplifier structures, filter fundamentals, and stability analysis.
Filters: Frequency Selective
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Covers frequency selective filters, focusing on a simple low-pass filter example and its practical applications.
Signal Acquisition: Stochastic Modeling
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Introduces signal acquisition, GMWM for sensor calibration, and the importance of accurate parameter matching.
Image Processing: Segmentation and Measurements
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Covers inverse Fourier transform, frequency filtering, segmentation, thresholding, particle size estimation, and analysis using ImageJ.
Signals & Systems I: Filter Equations and Poles
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Explores rational transfer functions, filter equations, poles, zeros, and impulse response in signal processing.
An Introduction to Signal Processing
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Covers the fundamentals of signal processing, analog-digital conversion, and applications of ADCs and DACs in environmental engineering.
Impulse-train Sampling: The Sampling Theorem
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Covers impulse-train sampling, the sampling theorem, and reconstructing signals from samples in the frequency domain.
Generators of Functions: Exercises
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Covers exercises related to generators of function circuits and their behavior.
Biomedical Microsystems: Fundamentals and Applications
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Covers the organization of the course, grading policy, bioelectricity, CMOS ICs, societal shifts, common medical measurands, and bioimplantable systems.
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