This report presents a tutorial of fundamental array processing and beamforming theory relevant to microphone array speech processing. A microphone array consists of multiple microphones placed at different spatial locations. Built upon a knowledge of sound propagation principles, the multiple inputs can be manipulated to enhance or attenuate signals emanating from particular directions. In this way, microphone arrays provide a means of enhancing a desired signal in the presence of corrupting noise sources. Moreover, this enhancement is based purely on knowledge of the source location, and so microphone array techniques are applicable to a wide variety of noise types. Microphone arrays have great potential in practical applications of speech processing, due to their ability to provide both noise robustness and hands-free signal acquisition.
標(biāo)簽： Microphone array Tutorial Array Signal Processing
上傳時(shí)間： 2016-06-12
上傳用戶：halias
Image processing third edition
標(biāo)簽： processing Image
上傳時(shí)間： 2017-02-17
上傳用戶：BIWE
Multiple-Input Multiple-Output (MIMO) systems have recently been the subject of intensive consideration in modem wireless communications as they offer the potential of providing high capacity, thus unleashing a wide range of applications in the wireless domain. The main feature of MIMO systems is the use of space-time processing and Space-Time Codes (STCs). Among a variety of STCs, orthogonal Space-Time Block Codes (STBCs) have a much simpler decoding method, compared to other STCs
標(biāo)簽： Orthogonal Space-Time Processing Complex
上傳時(shí)間： 2020-05-26
上傳用戶：shancjb
Optical communication technology has been extensively developed over the last 50 years, since the proposed idea by Kao and Hockham [1]. However, only during the last 15 years have the concepts of communication foundation, that is, the modulation and demodulation techniques, been applied. This is pos- sible due to processing signals using real and imaginary components in the baseband in the digital domain. The baseband signals can be recovered from the optical passband region using polarization and phase diversity tech- niques, as well as technology that was developed in the mid-1980s.
標(biāo)簽： Transmission Processing Digital Optical
上傳時(shí)間： 2020-05-27
上傳用戶：shancjb
OSCILLATORS are key building blocks in integrated transceivers. In wired and wireless communication terminals, the receiver front-end selects, amplifies and converts the desired high-frequency signal to baseband. At baseband the signal can then be converted into the digital domain for further data processing and demodula- tion. The transmitter front-end converts an analog baseband signal to a suitable high- frequency signal that can be transmitted over the wired or wireless channel.
標(biāo)簽： High-Frequency Oscillator Design
上傳時(shí)間： 2020-05-27
上傳用戶：shancjb
Driven by the desire to boost the quality of service of wireless systems closer to that afforded by wireline systems, space-time processing for multiple-input multiple-output (MIMO) wireless communications research has drawn remarkable interest in recent years. Excit- ing theoretical advances, complemented by rapid transition of research results to industry products and services, have created a vibrant and growing area that is already established by all counts. This offers a good opportunity to reflect on key developments in the area during the past decade and also outline emerging trends.
標(biāo)簽： Space-Time Processing
上傳時(shí)間： 2020-06-01
上傳用戶：shancjb
In this thesis several asp ects of space-time pro cessing and equalization for wire- less communications are treated. We discuss several di?erent metho ds of improv- ing estimates of space-time channels, such as temp oral parametrization, spatial parametrization, reduced rank channel estimation, b o otstrap channel estimation, and joint estimation of an FIR channel and an AR noise mo del. In wireless commu- nication the signal is often sub ject to intersymb ol interference as well as interfer- ence from other users.
標(biāo)簽： Communications Space-Time Processing Wireless for
上傳時(shí)間： 2020-06-01
上傳用戶：shancjb
Artificial Intelligence (AI) has undoubtedly been one of the most important buz- zwords over the past years. The goal in AI is to design algorithms that transform com- puters into “intelligent” agents. By intelligence here we do not necessarily mean an extraordinary level of smartness shown by superhuman; it rather often involves very basic problems that humans solve very frequently in their day-to-day life. This can be as simple as recognizing faces in an image, driving a car, playing a board game, or reading (and understanding) an article in a newspaper. The intelligent behaviour ex- hibited by humans when “reading” is one of the main goals for a subfield of AI called Natural Language Processing (NLP). Natural language 1 is one of the most complex tools used by humans for a wide range of reasons, for instance to communicate with others, to express thoughts, feelings and ideas, to ask questions, or to give instruc- tions. Therefore, it is crucial for computers to possess the ability to use the same tool in order to effectively interact with humans.
標(biāo)簽： Embeddings Processing Language Natural in
上傳時(shí)間： 2020-06-10
上傳用戶：shancjb
This edition of Digital Image Processing is a major revision of the book. As in the 1977 and 1987 editions by Gonzalez and Wintz, and the 1992, 2002, and 2008 editions by Gonzalez and Woods, this sixth-generation edition was prepared with students and instructors in mind. The principal objectives of the book continue to be to provide an introduction to basic concepts and methodologies applicable to digital image processing, and to develop a foundation that can be used as the basis for further study and research in this field. To achieve these objectives, we focused again on material that we believe is fundamental and whose scope of application is not limited to the solution of specialized problems. The mathematical complexity of the book remains at a level well within the grasp of college seniors and first-year graduate students who have introductory preparation in mathematical analysis, vectors, matrices, probability, statistics, linear systems, and computer programming. The book website provides tutorials to support readers needing a review of this background material
標(biāo)簽： Processing Digital Image
上傳時(shí)間： 2021-02-20
上傳用戶：
數(shù)字示波器功能強(qiáng)大,使用方便,但是價(jià)格相對昂貴。本文以Ti的MSP430F5529為主控器,以Altera公司的EP2C5T144C8 FPGA器件為邏輯控制部件設(shè)計(jì)數(shù)字示波器。模擬信號經(jīng)程控放大、整形電路后形成方波信號送至FPGA測頻,根據(jù)頻率值選擇采用片上及片外高速AD分段采樣。FPGA控制片外AD采樣并將數(shù)據(jù)輸入到FIFO模塊中緩存,由單片機(jī)進(jìn)行頻譜分析。測試表明:簡易示波器可以實(shí)現(xiàn)自動選檔、多采樣率采樣、高精度測頻及頻譜分析等功能。Digital oscilloscope is powerful and easy to use, but also expensive. The research group designed a low-cost digital oscilloscope, the chip of MSP430F5529 of TI is chosen as the main controller and the device of EP2C5T144C8 of Altera company is used as the logic control unit. Analog signal enter the programmable amplifier circuit, shaping circuit and other pre-processing circuit. The shaped rectangular wave signal is sent to FPGA for measure the frequency. According to the frequency value to select AD on-chip or off-chip high-speed AD for sampling. FPGA controls the off-chip AD sampling and buffers AD data by FIFO module. The single chip microcomputer receives the data, and do FFT for spectrum analysis. The test shows that the simple oscilloscope can realize automatic gain selection, sampling at different sampling rates, high precision frequency measurement and spectrum analysis.
標(biāo)簽： msp430 單片機(jī) fpga 數(shù)字示波器
上傳時(shí)間： 2022-03-27
上傳用戶：
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