'Filter output' presentation slideshows

Parallel FPGA Particle Filtering for Real-Time Neural Signal Processing

Parallel FPGA Particle Filtering for Real-Time Neural Signal Processing. John Mountney Co-advisors: Iyad Obeid and Dennis Silage. Outline. Introduction to Brain Machine Interfaces Decoding Algorithms Evaluation of the Bayesian Auxiliary Particle Filter

835 views • 71 slides

ECE 4331, Fall, 2009

ECE 4331, Fall, 2009. Zhu Han Department of Electrical and Computer Engineering Class 18 Oct. 27 th , 2007. Figure 5.1 Block diagram of a generic digital communication system. Figure 5.2 Additive white Gaussian noise (AWGN) model of a channel.

539 views • 45 slides

Lecture 12

576 views • 44 slides

1.94k views • 44 slides

Gravitational wave interferometer OPTICS

586 views • 40 slides

Baseband Receiver

Baseband Receiver. Receiver Design: Demodulation Matched Filter Correlator Receiver Detection Max. Likelihood Detector Probability of Error. Transmit and Receive Formatting. Sources of Error in received Signal. Major sources of errors: Thermal noise (AWGN)

1.82k views • 39 slides

Baseband Receiver

Baseband Receiver. Receiver Design: Demodulation Matched Filter Correlator Receiver Detection Max. Likelihood Detector Probability of Error. Transmit and Receive Formatting. Sources of Error in received Signal. Major sources of errors: Thermal noise (AWGN)

427 views • 39 slides

Introduction to GW from c ompact b inary c oalescence ( CBC )

372 views • 36 slides

Environmental Data Analysis with MatLab

Environmental Data Analysis with MatLab. Lecture 13: Filter Theory. SYLLABUS.

512 views • 35 slides

Tree-Based Density Clustering using Graphics Processors

410 views • 25 slides

Problem: Ground Clutter

Problem: Ground Clutter. Clutter: There is always clutter in signals and it distorts the purposeful component of the signal. Getting rid of clutter, or compensating for the loss caused by clutter might be possible by applying appropriate filtering and enhancing techniques.

375 views • 17 slides

Conclusions

Conclusions. Matthias Zwicker University of Bern. Properties of effective filters. Exploit auxiliary information from renderer Per-pixel features (normal, position, albedo, etc.) Support complex filter shapes Joint bilateral, NL-means filter Weighted local regression

63 views • 6 slides