| Tag |
First Indicator |
Second Indicator |
Subfields |
| LEADER |
00000ctm a22000005a 4500 |
| 001 |
in00001506021 |
| 005 |
20220103114456.0 |
| 007 |
cr unu a |
| 008 |
991029s1998 xx a b 000 0 eng d |
| 035 |
|
|
|9 AJL1321AM
|
| 035 |
|
|
|a (OCoLC)42729617
|
| 040 |
|
|
|a TXA
|c TXA
|d UtOrBLW
|
| 049 |
|
|
|a TXAM
|a TXAR
|
| 099 |
|
|
|a 1998
|a Thesis
|a L528
|
| 100 |
1 |
|
|a Li, Mu.
|
| 245 |
1 |
0 |
|a Neural networks for fast image compression /
|c by Mu Li.
|
| 264 |
|
1 |
|a [Place of publication not identified] :
|b [publisher not identified] ;
|c 1998.
|
| 300 |
|
|
|a x, 62 leaves :
|b illustrations ;
|c 28 cm.
|
| 336 |
|
|
|a text
|b txt
|2 rdacontent
|
| 337 |
|
|
|a computer
|b c
|2 rdamedia
|
| 338 |
|
|
|a online resource
|b cr
|2 rdacarrier
|
| 500 |
|
|
|a "Major subject: Electrical Engineering".
|
| 500 |
|
|
|a Vita.
|
| 502 |
|
|
|b M.S.
|c Texas A&M University
|d 1998.
|
| 504 |
|
|
|a Includes bibliographical references (leaves 42-44).
|
| 520 |
|
|
|a algorithm was adopted. In order to keep the
|
| 520 |
|
|
|a and decrease the number of neurons in the intermediate
|
| 520 |
|
|
|a aspects: compression ratio, image distortion, and
|
| 520 |
|
|
|a based on the predictive values and the input vectors.
|
| 520 |
|
|
|a compress a gray-scale image. The system consists of
|
| 520 |
|
|
|a compression part includes the input layer and the
|
| 520 |
|
|
|a compression ratio. Moreover, the parallel architecture
|
| 520 |
|
|
|a consists of the intermediate layer and the output
|
| 520 |
|
|
|a converge, an adaptive back-propagation learning
|
| 520 |
|
|
|a design of an image compression system involves three
|
| 520 |
|
|
|a fidelity of the image, such that at the receiver, the
|
| 520 |
|
|
|a for the learning process of the neural networks to
|
| 520 |
|
|
|a generalization capability of the compression system
|
| 520 |
|
|
|a good Peak-to-peak Signal to Noise Ratio and high
|
| 520 |
|
|
|a image, a set of natural networks instead of one
|
| 520 |
|
|
|a implement a new compression/decompression system to
|
| 520 |
|
|
|a inherent in the architecture of the neural networks
|
| 520 |
|
|
|a intermediate layer, while the decompression part
|
| 520 |
|
|
|a layer, a preprocessing element is designed which
|
| 520 |
|
|
|a layer. To gain high quality of the reconstructed
|
| 520 |
|
|
|a makes the compression system process very quickly.
|
| 520 |
|
|
|a network have been used in the system. Each neural
|
| 520 |
|
|
|a network was trained with some image blocks which have
|
| 520 |
|
|
|a number of bits transmitted as well as keeping the
|
| 520 |
|
|
|a performs the necessary' processing of the image before
|
| 520 |
|
|
|a predictor which predicts the current input block and a
|
| 520 |
|
|
|a processing speed. In this thesis, we design and
|
| 520 |
|
|
|a reconstructed image will have little distortion. The
|
| 520 |
|
|
|a similar characteristics. In order to decrease the time
|
| 520 |
|
|
|a subtracting element which generates residual vectors
|
| 520 |
|
|
|a The final results shows that the reconstructed image
|
| 520 |
|
|
|a The image compression system aims at reducing the graphics.
|
| 520 |
|
|
|a the image is encoded. The preprocessor includes a
|
| 520 |
|
|
|a three-layer feed forward neural networks. The
|
| 520 |
|
|
|a which was processed by our proposed scheme had a very
|
| 530 |
|
|
|a Also available online.
|
| 650 |
|
4 |
|a Major electrical engineering.
|
| 856 |
4 |
1 |
|u https://hdl.handle.net/1969.1/ETD-TAMU-1998-THESIS-L528
|z Link to OAKTrust copy
|t 0
|
| 999 |
|
|
|a MARS
|
| 999 |
f |
f |
|s 715f4fab-acef-32e9-9e9a-ed926059f160
|i e23f927c-4d85-3089-8f1d-3e656e221c04
|t 0
|
| 952 |
f |
f |
|p noncirc
|a Texas A&M University
|b College Station
|c Cushing Memorial Library & Archives
|s cush tdrm
|d Cushing: Theses & Dissertations Microforms (Does not check out)
|t 0
|e 1998 Thesis L528
|h Other scheme
|i computer -- online resource
|
| 952 |
f |
f |
|a Texas A&M University
|b College Station
|c Electronic Resources
|s www_evans
|d Available Online
|t 0
|e 1998 Thesis L528
|h Other scheme
|
| 998 |
f |
f |
|a 1998 Thesis L528
|t 0
|l Available Online
|
| 998 |
f |
f |
|a 1998 Thesis L528
|t 0
|l Cushing: Theses & Dissertations Microforms (Does not check out)
|