System and Method for Multi-Residue Multivariate Data Compression Page: 11
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US 9,026,506 B2
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cation, such as an operating system, and one or more lines of
code or other suitable software structures operating in a spe-
cific purpose software application.
Moduli-based coder system 402 receives data and encodes
the data using multi-residue multivariate compression. In one 5
exemplary embodiment, moduli-based coder system 402 uti-
lizes the algorithms disclosed herein, either in the form of
software-implemented algorithms operating on a suitable
platform, such as a general purpose processor, a parallel pro-
cessor or other suitable processors, or in the form of an 10
application-specific integrated circuit or other suitable cir-
cuitry. Moduli-based coder system 402 receives data, com-
presses or encodes the data using two or more moduli, and
transmits or stores the compressed or encoded data in a format
that allows the compressed data to be subsequently expanded is
or decoded. Moduli-based coder system 402 can thus be used
for a variety of applications, such as to compress audio data
for storage or transmission, to compress audiovisual or other
suitably changing data for storage or compression, to encrypt
data for secured storage or transmission as part of the process, 20
or for other suitable applications. These applications include
storage or streaming of data for delivery over a network,
streaming of audiovisual data for subsequent display on a
television or video display, streaming of audio data for sub-
sequent reproduction on speakers of a personal electronic 25
device such as a telephone or musical device, storage or
transmission of facsimiles, storage or transmission of still
images, storage or transmission of large files of information,
telecommunications, optical data transmission or storage,
financial data transmission or storage, or other suitable appli- 30
cations.
Moduli-based decoder system 404 receives encoded or
compressed data and decodes or expands the data using multi-
residue multivariate decoding or decompression. In one
exemplary embodiment, moduli-based decoder system 404 35
utilizes the algorithms disclosed herein, either in the form of
software-implemented algorithms operating on a suitable
platform, such as a general purpose processor, a parallel pro-
cessor or other suitable processors, or in the form of an
application-specific integrated circuit or other suitable cir- 40
cuitry. Moduli-based decoder system 404 can be utilized by
personal computers, tablet computers, telephones, personal
electronic devices, facsimile machines, televisions, stereo
systems, financial data processing systems or other suitable
devices. 45
Data storage system 406 receives encoded or compressed
data for storage and provides the encoded or compressed data
for use on demand. In one exemplary embodiment, data stor-
age system 406 utilizes a multi-residue multivariate frame
format for storage of encoded or compressed data. 50
Signal boundary analyzer 408 analyzes input data signals
to determine a boundary for the input data signals and amplify
or reduce the amplitude of the signal as it may be necessary
for the application. In one exemplary embodiment, the input
data signals may be in a format having variable boundaries 55
that can dynamically change from a large range between a
maximum and minimum value to a small range for a maxi-
mum and minimum value. Inthis exemplary embodiment, the
use of the disclosed multi-residue multivariate encoding or
compression processes can be optimized by selecting suitable 60
moduli for the associated boundary conditions, such as to
provide greater or lesser resolution, greater or lesser compres-
sion ratios, or other suitable parameters.
Moduli selector system 410 selects suitable moduli for use
in a multi-residue multivariate encoding or compression pro- 65
cess. In one exemplary embodiment, the moduli can be deter-mined as a function of the input data source, such as where a
12
predetermined data range and frame size is used. In another
exemplary embodiment, moduli selector can receive bound-
ary data for a signal from signal boundary analyzer 408 or
other suitable systems and can select an optimal set of moduli
for use with the associated boundary data. Moduli selector
system 410 can analyze the boundary data or other suitable
data in order to dynamically generate the associated moduli
using the processes disclosed herein, can utilize a look-up
table to select predetermined moduli, or can perform other
suitable processing.
Initial value and residue analyzer 412 analyzes input data
to generate initial value data and residue data in accordance
with the processes disclosed herein. In one exemplary
embodiment, initial value and residue analyzer 412 can select
one or more initial frames, sets, sequences, strings, series or
other data structure for use in calculation of the next trans-
mitted value, based on the transmitted residue one of one of
two or more moduli. Likewise, initial value and residue ana-
lyzer 412 can generate the residue values for the encoded or
compressed data, so as to allow the encoded or compressed
data to be decoded or expanded by moduli-based decoder
system 404, using the processes described herein. In one
exemplary embodiment, initial value and residue analyzer
412 can utilize one or more look-up tables to convert an input
data value of a signal into one or more residue values that can
be decoded and transmitted to moduli-based decoder system
404 and used to reproduce the input value based on the pre-
vious value of the signal.
Storage interface system 414 formats initial value and resi-
due data for storage. In one exemplary embodiment, storage
interface system 414 can assemble initial value moduli and
residue values into a data frame or other suitable formats
having a predetermined data structure, so as to allow the data
to be stored and subsequently retrieved by moduli-based
decoder system 404 or other suitable systems that can then
decode or decompress the data back into the original signal.
In another exemplary embodiment, storage interface system
414 can process data for storage in an optimal manner, such as
by buffering or otherwise storing the data and then subse-
quently compressing the data in an optimal data storage for-
mat, such as where real-time storage of the data is not
required, and where the optimal data storage format can be
obtained by processing the data independent of any real-time
data delivery requirements.
Data transmission system 416 formats moduli, initial value
field and residue data for transmission. In one exemplary
embodiment, data transmission system 416 can assemble
moduli, initial value field and residue values into a data frame
or other suitable formats having a predetermined data struc-
ture, so as to allow the data to be transmitted and subsequently
received by moduli-based decoder system 404 or other suit-
able systems that can then decode or decompress the data
back into the original signal. In another exemplary embodi-
ment, storage interface system 414 can process data for real-
time data transmission in an optimal manner, such as by
processing the data in a manner that can result in a less than
optimal compression ratio but which otherwise supports real-
time transmission, by processing the data in a manner to
optimize the data for dynamically changing bandwidth
requirements, or in other suitable manners.
Residue calculation system 418 receives data that has been
encoded or compressed using a multi-residue multivariate
encoding or compression process and decodes or expands the
data back to the original data signal, such as by using the
disclosed processes and those that utilize the nature of the
signal for compression using multi-residue compression andencryption. In one exemplary embodiment, residue calcula-
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Garcia, Oscar N.; Fu, Shengli & Jaganathan Melaedavattil, Jyothy. System and Method for Multi-Residue Multivariate Data Compression, patent, May 5, 2015; Washington, D.C.. (https://digital.library.unt.edu/ark:/67531/metadc991045/m1/11/: accessed July 18, 2024), University of North Texas Libraries, UNT Digital Library, https://digital.library.unt.edu; crediting UNT College of Engineering.