Compression for Quadratic Similarity Queries: Finite Blocklength and Practical Schemes


We tend to study the matter of compression for the aim of similarity identification, where similarity is measured by the mean square Euclidean distance between vectors. While the asymptotical elementary limits of the matter—the minimal compression rate and the error exponent—were found in a previous work, in this paper, we focus on the nonasymptotic domain and on practical, implementable schemes. We have a tendency to 1st present a finite blocklength achievability certain primarily based on shape-gain quantization: the gain (amplitude) of the vector is compressed via scalar quantization, and the shape (the projection on the unit sphere) is quantized employing a spherical code. The results are numerically evaluated, and that they converge to the asymptotic values, as predicted by the error exponent. We then offer a nonasymptotic lower bound on the performance of any compression scheme, and compare to the higher (achievability) certain. For a practical implementation of such a theme, we use wrapped spherical codes, studied by Hamkins and Zeger, and use the Leech lattice as an example for an underlying lattice. As a facet result, we tend to get a bound on the covering angle of any wrapped spherical code, as a perform of the covering radius of the underlying lattice.

Did you like this research project?

To get this research project Guidelines, Training and Code... Click Here

PROJECT TITLE : Deep Learning-Based Picture-Wise Just Noticeable Distortion Prediction Model for Image Compression ABSTRACT: Having a good eye for a picture An image processing technique known as Just Noticeable Difference, or
PROJECT TITLE : Learning a Single Tucker Decomposition Network for Lossy Image Compression With Multiple Bits-per-Pixel Rates ABSTRACT: A common problem in image processing is lossy image compression (LIC), which seeks to use
PROJECT TITLE : Wavelet-Based SpectralÎÜSpatial Transforms for CFA- Sampled Raw Camera Image Compression ABSTRACT: These spectral-spatial transforms (SSTs) are used to transform a raw camera image that was captured using a colour
PROJECT TITLE : Advanced Spherical Motion Model and Local Padding for 360 Video Compression ABSTRACT: The geometry distortion and the face boundary discontinuity are two of the key issues in 360Á video compression because of
PROJECT TITLE :Optimal Discrete Spatial Compression for Beamspace Massive MIMO Signals - 2018ABSTRACT:Deploying a large variety of antennas at the bottom station aspect can boost the cellular system performance dramatically.

Ready to Complete Your Academic MTech Project Work In Affordable Price ?

Project Enquiry