time frequency filtering 中文意思是什麼
time frequency filtering
解釋
時間頻率濾波-
The paper also studies fast arithmetic and programming of discrete time quadrature wt and wpt and takes a deep look into their additional applications in motor testing, including denoising, filtering and so on. starting from basic theory of time - frequency analysis and wavelet analysis of asymptotic signals, this paper investigates several if law extraction methods and presents an especially effective one using wavelet ridge
論文從時頻分析的基本理論出發，在漸進信號小波分析的基礎上，研究了漸進信號小波變換的漸進估計方法，提出了利用小波脊線來提取信號頻率隨時間連續變化規律（即瞬時頻率）的方法。 -
For slow targets whose doppler frequencies fall into clutter doppler band, the performance of frequency domain one - dimension filtering is seriously degraded. in an airborne radar, there is interdependence between the clutter doppler frequency and spatial position. space - time adaptive processing ( stap ) utilizes this interdependence to suppress clutter and get perfect main - lobe and side - lobe clutter suppression
空時自適應處理利用機載雷達地雜波多普勒頻率與地雜波空間位置的耦合性，根據目標和雜波在空間-多普勒頻域二維空間分佈上的差別對雜波進行抑制。 -
Frequency - domain gtls identification combined with time - frequency filtering for flight flutter modal parameter identification
基於時頻域濾波及頻域廣義整體最小二乘辨識的飛機顫振模態參數辨識 -
From theoretical analysis, we know the existing demodulation methods have limitations as following : one is that the subtraction of the two signals frequencies will display as the result of demodulation when we demodulate two time - domain adding signals without modulating information ( fault information ) ; the other one is that aliasing phenomenon will occur as a result of getting absolute value, detection or square in the process of generalized demodulation analysis, such phenomenon will result in some superfluous frequency composition on the frequency spectrum, which will puzzle the detec tion of mechanical vibration. if the sampling frequency is selected from a suitable range, the aliasing phenomenon will be avoided ; the last one is that aliasing frequencies will be produced in zoom demodulation analysis because this algorithm cannot employ digital low - pass filtering to avert the folding frequencies of higher harmonics in the process of zoom sub - sampling
現有的解調分析方法存在以下三種局限性：將不包括調制信息（故障信息）的兩時域相加信號，也以其頻率之差作為解調信號而解出；廣義檢波濾波解調分析中，由於取絕對值、檢波或平方過程可能產生混頻效應，在解調譜中表現為無法分析的頻率成分，並由此推導出避免這種混頻現象的采樣頻率的選取范圍，從根本上避免此類誤診斷的產生；幾種細化解調分析新演算法中，因為無法在細化分析的選抽時進行數字低通濾波，有可能會出現調制頻率的高次諧波成分發生頻率混疊而反折到低頻部分的現象。 -
The twelve kinds of modes and equivalent circuits within one high frequency switching period are carefully analyses. by using the state - space averaging approach, the converter ' s averaging model is presented, the output characteristic curve and design criterion of key circuit parameters such as output voltage, filtering inductance, common conduction time, uni - polarity spwm waveform ' s duty cycle etc are given
詳細分析了這類變換器在一個高頻開關周期內的十二個工作模式及其等效電路。採用狀態空間平均法建立了變換器平均模型，獲得了輸出電壓、濾波電感電流、共同導通時間、單極性spwm波占空比等關鍵電路參數的設計準則和變換器的外特性曲線。 -
Frequency - domain equalization. at the same time discusses some key problems in ofdm : high ratio of peak - to - average power of output signals, problem of synchronization, channel estimation, adaptive bit, power and subcarrier allocation. emphasize on channel estimation, and present a new algorithm which can filtering more interpolation errors and noise. for the sake of improve the performance of resist narrowband noise and make efficient use of the spectrum apply malvar wavelet division
同時就ofdm系統中的一些關鍵問題如峰值平均功率比（ papr ）太高，同步問題，通道估計，通道、比特與功率必須動態分配進行了研究，著重研究了通道估計問題並提出一種改進的方法，能濾除更多的噪聲分量和插值誤差，提高系統的性能；為了提高抗窄帶噪聲的性能和提高通道利用率，用malvar小波變換實現了不等帶寬分配。 -
Identification of nonlinear dynamic systems : time frequency filtering and skeleton curves
時頻濾波與骨架曲線 -
Wavelet has good localizing quality at time domain and frequency domain simultaneously and the characteristic of multi - resolution ratio analysis, so it can fulfill all kinds of wave - filtering needs such as low - pass, high - pass, sink wave, random noise denoising. compare with readitional wave - filtering methods, wavelet has incomparable advantage. wavelet has become an effective means of signal analysis and is intituled as math microscope of signal analysis
小波分析由於在時域頻域同時具有良好的局部化性質和多解析度分析的特點，因此不僅能滿足各種去噪要求如低通、高通、陷波、隨機噪音的去除等，而且與傳統的去噪方法相比較，有著無可比擬的優點，成為信號分析的一個強有力的工具，被譽為分析信號的數學顯微鏡。 -
This thesis mainly describes a tesing and consoling kit based on ni " s special virtual instrument software development kit - labwindows / cvi, aming at traditional testing device " s limitation such as high cost of hardware, complexity of construct, singleness of function etc. the tesing and consoling kit can condition the signal intermixed with interfere noise and deal with the collected datum through common signal conditioning ( amplification, isolation multiplex filtering ) -, software calibration digital filtering etc to analyse signal in time and frequency domain
本文針對傳統測量設備硬體成本高、構造復雜、重用性差、功能單一等方面的問題，著重探討了利用ni的labwindows cvi這一虛擬儀器開發軟體構建的測控平臺，通過通用信號調理（如放大、隔離、多路轉換、模擬濾波等） 、軟體校正、數字濾波等方法對混雜有干擾的信號進行調理及採集后的數據進行處理，然後進行時域或頻域的分析。 -
This text has finished the following several tasks mainly : first of all, through multianalysis and studying of the vibration theory of the gear wheel, draw the conclusion : effective time - frequency analysis is the inherent demand for analyzing the vibration signal of the gear wheel ; singularity monitoring and filtering the signal or depressing noise are the main applications of wavelet to gear wheel vibration signal analysis
本文主要完成了以下幾個任務：首先，通過對齒輪振動理論的全面分析與研究，得出結論：對齒輪振動信號進行有效的時頻分析是分析齒輪振動信號的內在需求；奇異性監測和對齒輪振動信號進行降噪濾波是小波變換在分析齒輪振動信號的主要應用。 -
The signals are transformed into digital signals and sent to a computer. digital signal processing includes amplifying the sound signals, low - pass filtering, wavelet transform for de - noise and analyzing power spectra using matlab software. for different species of pests the acoustic characteristics are different in time domain and frequency domain
害蟲聲信號採集系統由日本產teac ；四通道錄音機（數字記錄儀）記錄害蟲爬行聲信號，數字示波器將聲信號轉變為數字信號送計算機存儲，由matlab軟體對數據文件進行信號處理，包括信號的再現、放大、濾波、小波去噪、功率譜分析等工作。 -
Therefore, based on the ann correlation signal post - processing technique, we designed a kind of sdf performed in spatial domain, and a two - step recognition technique was introduced to perform real - time distortion - invariant recognition by combining frequency domain filtering of sdf with spatial domain filtering of sdf
為此，本文在ann相關信號后處理技術的基礎上引入了二次識別技術，設計製作了一種空域執行的sdf濾波器，採用頻域sdf濾波與空域sdf濾波相結合的方法，對目標進行實時畸變不變識別。 -
The principle and characteristics of ofdm system are introduced first. then several key technologies of channel estimation and equalization for ofdm are discussed in detail, including pilot signal based channel estimation methods, cyclic prefix based channel estimation method, frequency domain adaptive filtering method and time domain equalization method for long channel impulse. the corresponding comparison and simulations are also provided
文中討論了利用導頻信號的通道估計方法，利用循環前綴進行通道估計的方法， ofdm信號均衡中自適應濾波技術，及通道沖擊響應長于循環前綴時利用時域均衡減少解調器輸入信號拖尾長度的方法，分析了這些方法的原理，並通過計算機模擬驗證了這些方法的性能。 -
That is by inserting known symbols or pilots in time and frequency domain to estimate the channel frequency response. the proposed method employs iterative low - pass filtering in transform domain which can reduce additive white gaussian noise and inter - carrier interference effectively
該估計演算法採用在變換域多次迭代濾波的方式，能夠顯著降低高斯噪聲和載波間干擾（ ici ）對估計性能的影響，同時快速fft演算法也使得變換域濾波變得比較簡便。 -
It ' s a problem of great significance how to filtering a signal in joint time - frequency domain and reconstruct the time series from the time - frequency plane selected. in this thesis, the theory of joint time - frequency analysis and synthesis and time - frequency filtering is investigated. two kinds of new time - frequency domain filtering methods are proposed based on adaptive decomposition and linear subspace projection
本文在系統學習現有的各種時頻分析及其綜合演算法的基礎上，詳細研究了時頻域濾波的核心思想和基本方法，吸取了自適應時頻分析和線性子空間投影wigner - ville變換的優點，提出了的兩種新的時頻域濾波方法，並通過理論分析和數字模擬完成了相應的數值特性與應用特性研究。 -
Besed on wavelet " s well localized characterizes in time frequency and space frequency, we can exactly depict events of nonnoise by decomposing to signal using binary - wavelet transform. for events of noise, local max can be found at singular points of signal by using wavelet transform norm of signal, so adopting multiscale wavelet analysis the maximal point of wavelet transform norm, which risen by the noise, with increasing of scale, which rien by the fault appeared. gived a properly threshold and compared the relation of data that have been transformed not only find the fault in the low noise signal but also resume the signal by filtering noise, which have good power of examining singular signal being unexpectedly change
對于噪聲中的事件點，利用信號的小波變換的模在信號的突變點取得局部最大值，採用多尺度（多分辨）小波分析，則隨著尺度的增大，噪聲引起的小波變換模的極大值點迅速減少，而故障引起的小波變換模的極大值點得以顯露，我們給出一個適當的閥值，比較閥值和變換后數據的關系，不但可以在低信噪比的信號中監測到故障信號，而且可以濾去噪聲恢復原信號，對突變的奇異性信號具有良好的監測能力，能夠有效地找出噪聲中的事件點。
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