例句與造句

1. In our proposed method , both the objective function and the perfect reconstruction condition are expressed as a quadratic function of the prototype filter coefficient vector
   該方法中，目標(biāo)函數(shù)和完全重構(gòu)條件均被表示成為原型濾波器系數(shù)矢量的二次函數(shù)形式。
2. By using the lagrange multiplier approach , the design procedure is formulated as solving the linear equation iteratively to obtain the desirable prototype filter coefficient vector
   使用拉格朗日乘數(shù)方法，算法通過迭代求解線性方程來獲得期望的原型濾波器系數(shù)矢量。
3. We raised a new model that we disassemble the character into several parts , which could be recognized by computer topologically based on the high - frequency wavelet coefficients vector , disregarding the traditional extraction method that used the statistical or structural feature based on the individual pixel in the 2 - dim plane of character . moreover , the concept of multi - dim cognizing feature model was put forward by encoding the character , according to its " location and run - length information . the information confusion and redundancy could be largely eliminated , as leaded to the improving of the preciseness when recognizing the character
   克服以往結(jié)構(gòu)、統(tǒng)計(jì)方法在字符特征提取中無法剔除噪聲、偏移等冗余信息的不足，以認(rèn)知的新思路分析圖像，給出基于小波子圖的筆劃定義，給出一種注重反映字符部分最為重要的筆劃的類型、數(shù)量、游程、位置特征，改進(jìn)了基于字符二維圖像的統(tǒng)計(jì)與結(jié)構(gòu)特征提取方法因變形，畸變造成信息混淆和冗余；給出了提取多屬性字符認(rèn)知特征的方法和識別機(jī)制，實(shí)驗(yàn)表明，該方法能有效的識別字符； 3
4. The inner product of the mapping value of the original data in feature space is replaced by a kernel function , and the weights of each neuron can be initialized and updated by initializing and updating the combinatorial coefficient vector of each weight in the algorithm of ksom , so some intuitive and simple iteration formulas are obtained
   該算法以核函數(shù)代替原始數(shù)據(jù)在特徵空間中映射值的內(nèi)積，并且神經(jīng)元權(quán)值向量的初始化和更新都可由其組合系數(shù)向量表示，從而獲得了直觀而簡單的迭代公式。
5. Chapter four introduces the basic theories of continue hidden markov models ( chmm ) . the new method of faults diagnosis based mixture density chmms directly by the vibration ar coefficients vectors of rotating machine is proposed , and then the dynamic patterns presented in run - up process of rotor machine are successfully recognized . at last compares the two faults diagnosis methods of dhmm and chmm , and points out the advantages and disadvantages of the two methods
   第四章：在連續(xù)隱markov模型( chmm )的基本理論基礎(chǔ)上，提出了直接利用振動(dòng)信號ar系數(shù)特征矢量序列建立混合密度chmm的故障診斷新方法，并對轉(zhuǎn)子升速過程的振動(dòng)模式進(jìn)行了成功的識別；對dhmm和chmm故障診斷方法進(jìn)行了對比分析，指出dhmm方法具有算法穩(wěn)定、計(jì)算速度快、識別精度高等特點(diǎn)，對于chmm方法只要通過合理選擇特征參數(shù)也能得到高的識別精度。
6. It's difficult to find coefficient vector in a sentence. 用coefficient vector造句挺難的