國立高雄大學圖資館 |

登入

回首頁

The regularized fast Hartley transformlow-complexity parallel computation of the FHT in one and multiple dimensions /

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	The regularized fast Hartley transformby Keith John Jones.
其他題名:	low-complexity parallel computation of the FHT in one and multiple dimensions /
作者:	Jones, Keith John.
出版者:	Cham :Springer International Publishing :2022.
面頁冊數:	xix, 320 p. :ill., digital ;24 cm.
Contained By:	Springer Nature eBook
標題:	Hartley transforms.
電子資源:	https://doi.org/10.1007/978-3-030-68245-3
ISBN:	9783030682453$q(electronic bk.)

The regularized fast Hartley transformlow-complexity parallel computation of the FHT in one and multiple dimensions /
Jones, Keith John.

The regularized fast Hartley transformlow-complexity parallel computation of the FHT in one and multiple dimensions /[electronic resource] :by Keith John Jones. - Second edition. - Cham :Springer International Publishing :2022. - xix, 320 p. :ill., digital ;24 cm.

Part 1: The Discrete Fourier and Hartley Transforms -- Background to Research -- The Real-Data Discrete Fourier Transform -- The Discrete Hartley Transform -- Part 2: The Regularized Fast Hartley Transform -- Derivation of Regularized Formulation of Fast Hartley Transform -- Design Strategy for Silicon-Based Implementation of Regularized Fast Hartley Transform -- Architecture for Silicon-Based Implementation of Regularized Fast Hartley Transform -- Design of CORDIC-Based Processing Element for Regularized Fast Hartley Transform -- Part 3: Applications of Regularized Fast Hartley Transform -- Derivation of Radix-2 Real-Data Fast Fourier Transform Algorithms using Regularized Fast Hartley Transform -- Computation of Common DSP-Based Functions using Regularized Fast Hartley Transform -- Part 4: The Multi-Dimensional Discrete Hartley Transform -- Parallel Reordering and Transfer of Data between Partitioned Memories of Discrete Hartley Transform for 1-D and m-D Cases -- Architectures for Silicon-Based Implementation of m-D Discrete Hartley Transform using Regularized Fast Hartley Transform -- Part 5: Results of Research -- Summary and Conclusions.

This book describes how a key signal/image processing algorithm - that of the fast Hartley transform (FHT) or, via a simple conversion routine between their outputs, of the real‑data version of the ubiquitous fast Fourier transform (FFT) - might best be formulated to facilitate computationally-efficient solutions. The author discusses this for both 1-D (such as required, for example, for the spectrum analysis of audio signals) and m‑D (such as required, for example, for the compression of noisy 2-D images or the watermarking of 3-D video signals) cases, but requiring few computing resources (i.e. low arithmetic/memory/power requirements, etc.) This is particularly relevant for those application areas, such as mobile communications, where the available silicon resources (as well as the battery-life) are expected to be limited. The aim of this monograph, where silicon‑based computing technology and a resource‑constrained environment is assumed and the data is real-valued in nature, has thus been to seek solutions that best match the actual problem needing to be solved.

ISBN: 9783030682453$q(electronic bk.)

Standard No.: 10.1007/978-3-030-68245-3doiSubjects--Topical Terms:

485447
Hartley transforms.

LC Class. No.: QA403.5 / .J66 2022

Dewey Class. No.: 515.723

The regularized fast Hartley transformlow-complexity parallel computation of the FHT in one and multiple dimensions /
LDR:03347nmm a2200349 a 4500 001 617843
003 DE-He213
005 20210903012326.0
006 m d
007 cr nn 008maaau
008 221025s2022 sz s 0 eng d
020 $a 9783030682453$q(electronic bk.)
020 $a 9783030682446$q(paper)
024 7 $a 10.1007/978-3-030-68245-3 $2 doi
035 $a 978-3-030-68245-3
040 $a GP $c GP
041 0 $a eng
050 4 $a QA403.5 $b .J66 2022
072 7 $a TTBM $2 bicssc
072 7 $a TEC008000 $2 bisacsh
072 7 $a TTBM $2 thema
072 7 $a UYS $2 thema
082 0 4 $a 515.723 $2 23
090 $a QA403.5 $b .J77 2022
100 1 $a Jones, Keith John. $3 917442
245 1 4 $a The regularized fast Hartley transform $h [electronic resource] : $b low-complexity parallel computation of the FHT in one and multiple dimensions / $c by Keith John Jones.
250 $a Second edition.
260 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2022.
300 $a xix, 320 p. : $b ill., digital ; $c 24 cm.
505 0 $a Part 1: The Discrete Fourier and Hartley Transforms -- Background to Research -- The Real-Data Discrete Fourier Transform -- The Discrete Hartley Transform -- Part 2: The Regularized Fast Hartley Transform -- Derivation of Regularized Formulation of Fast Hartley Transform -- Design Strategy for Silicon-Based Implementation of Regularized Fast Hartley Transform -- Architecture for Silicon-Based Implementation of Regularized Fast Hartley Transform -- Design of CORDIC-Based Processing Element for Regularized Fast Hartley Transform -- Part 3: Applications of Regularized Fast Hartley Transform -- Derivation of Radix-2 Real-Data Fast Fourier Transform Algorithms using Regularized Fast Hartley Transform -- Computation of Common DSP-Based Functions using Regularized Fast Hartley Transform -- Part 4: The Multi-Dimensional Discrete Hartley Transform -- Parallel Reordering and Transfer of Data between Partitioned Memories of Discrete Hartley Transform for 1-D and m-D Cases -- Architectures for Silicon-Based Implementation of m-D Discrete Hartley Transform using Regularized Fast Hartley Transform -- Part 5: Results of Research -- Summary and Conclusions.
520 $a This book describes how a key signal/image processing algorithm - that of the fast Hartley transform (FHT) or, via a simple conversion routine between their outputs, of the real‑data version of the ubiquitous fast Fourier transform (FFT) - might best be formulated to facilitate computationally-efficient solutions. The author discusses this for both 1-D (such as required, for example, for the spectrum analysis of audio signals) and m‑D (such as required, for example, for the compression of noisy 2-D images or the watermarking of 3-D video signals) cases, but requiring few computing resources (i.e. low arithmetic/memory/power requirements, etc.) This is particularly relevant for those application areas, such as mobile communications, where the available silicon resources (as well as the battery-life) are expected to be limited. The aim of this monograph, where silicon‑based computing technology and a resource‑constrained environment is assumed and the data is real-valued in nature, has thus been to seek solutions that best match the actual problem needing to be solved.
650 0 $a Hartley transforms. $3 485447
650 1 4 $a Signal, Image and Speech Processing. $3 273768
650 2 4 $a Theory of Computation. $3 274475
650 2 4 $a Communications Engineering, Networks. $3 273745
710 2 $a SpringerLink (Online service) $3 273601
773 0 $t Springer Nature eBook
856 4 0 $u https://doi.org/10.1007/978-3-030-68245-3
950 $a Engineering (SpringerNature-11647)