n recent years, there have been many books published on power system optimization.
Most of these books do not cover applications of artifi cial intelligence based methods.
Moreover, with the recent increase of artifi cial intelligence applications in various fi elds,
it is becoming a new trend in solving optimization problems in engineering in general
due to its advantages of being simple and effi cient in tackling Complex problems. For this
reason, the application of artifi cial intelligence in power systems has attracted the interest
of many researchers around the world during the last two decades. This book is a result
of our effort to provide information on the latest applications of artifi cial intelligence
to optimization problems in power systems before and after deregulation.
We’re living through exciting times. The landscape of what computers can do is
changing by the week. Tasks that only a few years ago were thought to require
higher cognition are getting solved by machines at near-superhuman levels of per-
formance. Tasks such as describing a photographic image with a sentence in idiom-
atic English, playing Complex strategy game, and diagnosing a tumor from a
radiological scan are all approachable now by a computer. Even more impressively,
computers acquire the ability to solve such tasks through examples, rather than
human-encoded of handcrafted rules.
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.
The present era of research and development is all about interdisciplinary studies
attempting to better comprehend and model our understanding of this vast universe.
The fields of biology and computer science are no exception. This book discusses
some of the innumerable ways in which computational methods can be used to
facilitate research in biology and medicine—from storing enormous amounts of
biological data to solving Complex biological problems and enhancing the treatment
of various diseases.
Current field forecast verification measures are inadequate, primarily because they compress the comparison
between two Complex spatial field processes into one number. Discrete wavelet transforms (DWTs) applied to
analysis and contemporaneous forecast fields prove to be an insightful approach to verification problems. DWTs
allow both filtering and compact physically interpretable partitioning of fields. These techniques are used to
reduce or eliminate noise in the verification process and develop multivariate measures of field forecasting
performance that are shown to improve upon existing verification procedures.
基于FPGA設計的相關論文資料大全 84篇用FPGA實現FFT的研究
劉朝暉 韓月秋
摘 要 目的 針對高速數字信號處理的要求，給出了用現場可編程門陣列(FPGA)實現的
快速傅里葉變換(FFT)方案.方法 算法為按時間抽取的基4算法，采用遞歸結構的塊浮點運
算方案，蝶算過程只擴展兩個符號位以適應雷達信號處理的特點，乘法器由陣列乘法器實
現.結果 采用流水方式保證系統的速度，使取數據、計算旋轉因子、復乘、DFT等操作協
調一致，在計算、通信和存儲間取得平衡，避免了瓶頸的出現.結論 實驗表明，用FPGA
實現高速數字信號處理的算法是一個可行的方案.
關鍵詞 離散傅里葉變換； 快速傅里葉變換； 塊浮點運算； 可編程門陣列
分類號 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
針對目前MSP430單片機實驗裝置較少、實驗內容少,而且無MSP430高端產品的實驗裝置,研制了基于MSP430F5529單片機的綜合實驗裝置,主要包括MSP430 Launch Pad和母板兩部分。較傳統的單片機實驗裝置增加了模擬電路的設置,設計的實驗能夠利用單片機的所有外設,可進行模塊基礎實驗和綜合實驗兩大類實驗,非常適合自動化和電氣信息類大學生學習使用。Concerning with the lack of experimental equipment and content based on MSP430,and especially,the experimental equipment of MSP430 senior products,an experimental equipment based on MSP430F5529 microcontroller is developed. It mainly consists of two parts： MSP430 Launch Pad and main board. Compared with traditional microcontroller experiment equipment,a few analog circuits were added. The experiment we set up takes advantage of all microcontroller peripherals. Students can do two kinds of experiments： module experiment and Complex experiment.Therefore it fits university students in automation and electrical major very well.
針對交流電路過零檢測電路存在結構復雜、過零點檢測不準確、編程繁瑣等問題，設計了一種基于LM339的硬件結構簡單的過零檢測電路。通過仿真軟件Mulisim對該設計電路進行了仿真，實驗證明了該方案過零檢測的可行性、穩定性和可靠性，可直接作為交流電路中CPU的過零信號。Aiming at the problems of AC cilsuit zero crossing detection circuit such as Complex structure, zero crossing detection and cumbersome programming, a zero crossing detection circuit with simple hardware structure based on LM339 was designed. The design circuit was simulated by simulation software Mulisim, and the feasibility, stability and reliability of zero crossing detection were proved by experiments, which can be used as zero crossing signal of CPU in AC circuit directly.
這是一本英文版的MPC的MATLAB教程，講這一塊的資料太少了，故上傳一本。MPC is one of the few areas that has received on-going interest from researchers in both the industrial and cademic communities.Four major aspects of model predictive control make the design methodology attractive to both practitioners and academics.This is particularly attractive to industry where tight profit margins and limits on the process operation are inevitably present. The third aspect is the ability to perform on-line process optimization. The fourth aspect is the simplicity of the design framework in handling all these Complex issues.
