Reliable and accurate positioning and navigation is critical for a diverse set of emerging applications
calling for advanced signal-Processing techniques. This book provides an overview of some of the
most recent research results in the field of signal processing for positioning and navigation, addressing
many challenging open problems.
This paper presents a Hidden Markov Model (HMM)-based speech
enhancement method, aiming at reducing non-stationary noise from speech
signals. The system is based on the assumption that the speech and the noise
are additive and uncorrelated. Cepstral features are used to extract statistical
information from both the speech and the noise. A-priori statistical
information is collected from long training sequences into ergodic hidden
Markov models. Given the ergodic models for the speech and the noise, a
compensated speech-noise model is created by means of parallel model
combination, using a log-normal approximation. During the compensation, the
mean of every mixture in the speech and noise model is stored. The stored
means are then used in the enhancement process to create the most likely
speech and noise power spectral distributions using the forward algorithm
combined with mixture probability. The distributions are used to generate a
Wiener filter for every observation. The paper includes a performance
evaluation of the speech enhancer for stationary as well as non-stationary
noise environment.
In this book we focus on the basic signal processing that underlies current and
future ultra wideband systems. By looking at signal processing in this way we
hope this text will be useful even as UWB applications mature and change or
regulations regarding ultra wideband systems are modified. The current UWB
field is extremely dynamic, with new techniques and ideas being presented at every
communications and signal-Processing conference. The basic signal-Processing
techniques presented in this text though will not change for some time to come.
Thus, we have taken a somewhat theoretical approach, which we believe is longer
lasting and more useful to the reader in the long term than an up-to-the-minute
summary that is out of date as soon as it is published.
Wireless communications, together with its applications and underlying technologies, is
among today’s most active areas of technology development. The very rapid pace of im-
provements in both custom and programmable integrated circuits for signal processing ap-
plications has led to the justfiable view of advanced signal processing as a key enabler of the
aggressively escalating capacity demands of emerging wireless systems. Consequently, there
has been a tremendous and very widespread effort on the part of the research community
to develop novel signal processing techniques that can fulfill this promise.
Digital radios have undergone an astonishing evolution in the last century. Born as a set of simple and
power-hungry electrical and electromechanical devices for low data rate transmission of telegraph data
in the Marconi age, they have transformed, thanks to substantial advances in electronic technology,
into a set of small, reliable and sophisticated integrated devices supporting broadband multimedia
communications. This, however, would not have been possible unless significant progress had been
made in recent decades in the field of signal processing algorithms for baseband and passband signals.
In fact, the core of any modern digital radio consists of a set of algorithms running over programmable
electronic hardware. This book stems from the research and teaching activities of its co-authors in
the field of algorithmic techniques for wireless communications. A huge body of technical literature
has accumulated in the last four decades in this area, and an extensive coverage of all its important
aspects in a single textbook is impossible. For this reason, we have selected a few important topics
and, for ease of reading, organized them into two parts.
The author’s group has developed various chipless RFID tags and reader architectures
at 2.45, 4–8, 24, and 60 GHz. These results were published extensively in the form of
books, book chapters, refereed conference and journal articles, and finally, as patent
applications. However, there is still room for improvement of chipless RFID sys-
tems. In this book, we proposed advanced techniques of chipless RFID systems that
supersede their predecessors in signal processing, tag design, and reader architecture.
Identification is pervasive nowadays in daily life due to many complicated activities such as
bank and library card reading, asset tracking, toll collecting, restricted access to sensitive data
and procedures and target identification. This kind of task can be realized by passwords, bio-
metric data such as fingerprints, barcode, optical character recognition, smart cards and radar.
Radiofrequencyidentification(RFID)isatechniquetoidentifyobjectsbyusingradiosystems.
It is a contactless, usually short distance, wireless data transmission and reception technique
for identification of objects. An RFID system consists of two components: the tag (also called
transponder) and the reader (also called interrogator).
基于FPGA設(shè)計(jì)的相關(guān)論文資料大全 84篇用FPGA實(shí)現(xiàn)FFT的研究
劉朝暉 韓月秋
摘 要 目的 針對(duì)高速數(shù)字信號(hào)處理的要求,給出了用現(xiàn)場(chǎng)可編程門陣列(FPGA)實(shí)現(xiàn)的
快速傅里葉變換(FFT)方案.方法 算法為按時(shí)間抽取的基4算法,采用遞歸結(jié)構(gòu)的塊浮點(diǎn)運(yùn)
算方案,蝶算過(guò)程只擴(kuò)展兩個(gè)符號(hào)位以適應(yīng)雷達(dá)信號(hào)處理的特點(diǎn),乘法器由陣列乘法器實(shí)
現(xiàn).結(jié)果 采用流水方式保證系統(tǒng)的速度,使取數(shù)據(jù)、計(jì)算旋轉(zhuǎn)因子、復(fù)乘、DFT等操作協(xié)
調(diào)一致,在計(jì)算、通信和存儲(chǔ)間取得平衡,避免了瓶頸的出現(xiàn).結(jié)論 實(shí)驗(yàn)表明,用FPGA
實(shí)現(xiàn)高速數(shù)字信號(hào)處理的算法是一個(gè)可行的方案.
關(guān)鍵詞 離散傅里葉變換; 快速傅里葉變換; 塊浮點(diǎn)運(yùn)算; 可編程門陣列
分類號(hào) TP39; TN957.511
Implementation of FFT with FPGA Technology
Liu Zhaohui Han Yueqiu
(Department of Electronics Engineering, Beijing Institute of Technology, Beijing 100081)
Abstract Aim To propose a scheme for implementing FFT with FPGA in accor-dance with the
requirement for high speed digital signal processing. Methods The structure of FPGA and
requirement of system were considered in the experiment, radix-4 algorithm of DIT and recursive
structure were adopted. The group float point arithmetic operation was used in the butterfly and the
array multiplier was used to realize multiplication. Results The pipeline pattern was used to ensure
the system speed, it made fetching data, calculating twiddle factor, complex multiplication and D
本系統(tǒng)采用電動(dòng)機(jī)電樞供電回路串接采樣電阻的方式來(lái)實(shí)現(xiàn)對(duì)小型直流有刷電動(dòng)機(jī)的轉(zhuǎn)速測(cè)量。該系統(tǒng)主要由二階低通濾波電路,小信號(hào)放大電路、單片機(jī)測(cè)量顯示電路、開(kāi)關(guān)穩(wěn)壓電源電路等組成。同時(shí)自制電機(jī)測(cè)速裝置,用高頻磁環(huán)作為載體,用線圈繞制磁環(huán),利用電磁感應(yīng)原理檢測(cè)電機(jī)運(yùn)行時(shí)的漏磁,將變化的磁場(chǎng)信號(hào)轉(zhuǎn)化為磁環(huán)上的感應(yīng)電流。用信號(hào)處理單元電路將微弱電信號(hào)轉(zhuǎn)化為脈沖信號(hào),送由單片機(jī)檢測(cè),從而達(dá)到準(zhǔn)確測(cè)量電機(jī)的速度的要求。In this system, the sampling resistance of armature power supply circuit is connected in series to measure the speed of small DC brush motor. The system is mainly composed of second-order low-pass filter circuit, small signal amplifier circuit, single-chip measurement and display circuit, switching regulated power supply circuit and so on. At the same time, the self-made motor speed measuring device uses high frequency magnetic ring as the carrier, coil winding magnetic ring, and electromagnetic induction principle to detect the leakage of magnetic field during the operation of the motor, which converts the changed magnetic field signal into the induced current on the magnetic ring. The weak electric signal is transformed into pulse signal by signal processing unit circuit, which is sent to single chip computer for detection, so as to meet the requirement of accurate measurement of motor speed.