Search - Rank-P

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[Other] Detection of Rank-P Signal DL : 0: Detection of Rank-P signals
Update : 2012-02-22 Size : 830.5kb Publisher : chenpeng3361
[Algorithm] iml DL : 0: IML package provides efficient routines to solve nonsingular systems of linear equations, certified solve any shape systems of linear equations, and perform mod p matrix operations, such as computing row-echelon form, determinant, rank profile, inverse of a mod p matrix.
Update : 2025-02-19 Size : 402kb Publisher : nibber
[SCM] LCD_Compatible_search DL : 0: This program will help you to find out which LCD (for Mobile Phones) is compatible with each other . enjoy :P don t forget to rank me :P
Update : 2025-02-19 Size : 305kb Publisher : Mike
[Algorithm] single DL : 0: 一般性的奇异值分解算法，float浮点型。-SGGSVD computes the generalized singular value decomposition (GSVD) * of an M-by-N real matrix A and P-by-N real matrix B: * * U*A*Q = D1*( 0 R ), V*B*Q = D2*( 0 R ) * * where U, V and Q are orthogonal matrices, and Z is the transpose * of Z. Let K+L = the effective numerical rank of the matrix (A ,B ) , * then R is a K+L-by-K+L nonsingular upper triangular matrix, D1 and * D2 are M-by-(K+L) and P-by-(K+L) "diagonal" matrices and of the * following structures,
Update : 2025-02-19 Size : 36kb Publisher : muxihan
[matlab] fecgm DL : 0: 独立成份分析（ＩＣＡ）以及ｗｉｎｎｅｒ滤波 Source separation of complex signals with JADE. Jade performs `Source Separation in the following sense: X is an n x T data matrix assumed modelled as X = A S + N where o A is an unknown n x m matrix with full rank. o S is a m x T data matrix (source signals) with the properties a) for each t, the components of S(:,t) are statistically independent b) for each p, the S(p,:) is the realization of a zero-mean `source signal . c) At most one of these processes has a vanishing 4th-order cumulant. o N is a n x T matrix. It is a realization of a spatially white Gaussian noise, i.e. Cov(X) = sigma*eye(n) with unknown variance sigma. This is probably better than no modeling at a- Source separation of complex signals with JADE. Jade performs `Source Separation in the following sense: X is an n x T data matrix assumed modelled as X = A S+ N where o A is an unknown n x m matrix with full rank. o S is a m x T data matrix (source signals) with the properties a) for each t, the components of S(:,t) are statistically independent b) for each p, the S(p,:) is the realization of a zero-mean `source signal . c) At most one of these processes has a vanishing 4th-order cumulant. o N is a n x T matrix. It is a realization of a spatially white Gaussian noise, i.e. Cov(X) = sigma*eye(n) with unknown variance sigma. This is probably better than no modeling at all...
Update : 2025-02-19 Size : 7kb Publisher : 王庆香
[matlab] OFDMoncha DL : 1: . 对于基于块状（block-type）导频的信道估计，仿真实现LS， LMMSE modified 和基于SVD的降维LMMSE 算法在多径频率选择性特征的信道上的BER VS SNR 和BER VS Doppler frequency shift 的功能。 2. 对于基于梳状（comb-type）导频的信道估计，实现LS with 1D linear interpolation, LS with second-order interpolation, LS with Spline cubic interpolation. 3. 比较块状和梳妆导频信道估计方法在不同的特征的信道上的性能（channel with fast fading and channel with slow fading）. 4. 信号的调制方式可以选择16QAM或者QPSK 5.对于SVD-LMMSE （optimal rank reduction）, rank的取值P也会的到分析。
Update : 2013-05-13 Size : 2.4kb Publisher : xiongsj715@163.com
[Data structs] temperature DL : 0: 择使用数组储存数据。*x,*y分别装入观察站的地理坐标，temp装入的是温度信息，*tpx,*tpy分别用作对x,y进行快速排序（tpx[2]=8表示排在第2位的是x[8],rank[8]=2表示x[8]排在第2位）升序，rankx[i]即为最终x[i]的排名。为了方便计算一个范围内的温度值，定义了一个long long 型的数组sum。算出比点p小的点(不包括点p本身)的所有温度值之和sum，之后范围的四点sum相加减,再对少数点做处理即可得到范围内的温度之和。sum[i][j]表示的是rankx=i,ranky=j左下方的温度之和，相当于一个hashtable（映射关系）-Optional use arrays to store data.* X,* y respectively, into the geographical coordinates of the Observatory, temp temperature information is loaded,* tpx,* tpy respectively used for x, y quick sort (tpx [2] = 8 means that in the first two rows of the is x [8], rank [8] = 2 means that x [8] ranked No. 2) ascending, rankx [i] shall be final and x [i] in the rankings. In order to facilitate the calculation of the temperature within a range that defines a long long type array sum. Point p is smaller than the calculated points (not including the point p itself) of all temperature values and the sum, sum the four points of the range after the addition and subtraction, then do not handle a small number of points can be obtained and a temperature within the range. sum [i] [j] represents the rankx = i, ranky = j the temperature of the lower left, the equivalent of a hashtable (mappings)
Update : 2025-02-19 Size : 3kb Publisher : 周嘉莉
[Other] L-to-R-for-I--R-and-N--L--P DL : 0: 自然语言处理，希望对相关领域研究人员有所帮助-Learning to Rank for Information Retri and Natural Language Processing
Update : 2025-02-19 Size : 3.06mb Publisher : 虚怀若谷
[JSP/Java] PageRank DL : 0: PR值收敛的证明再次不做过多赘述，但是需要注意的是，PR值收敛的一个必要条件是矩阵A需要满足每一列的元素和都为1。如果开始时P向量中各部分值之和为一，那么在精度能够保证的情况下，每次迭代之后P向量中各部分的值之和依然是一，而每次迭代可以看成是对P向量中各部分值重新分配的过程。矩阵A中第i列的数据可以看成是第i个节点引用其他节点的概率，这些数据决定了第i个节点的PR值如何分配给其他所有节点。(a realization of page rank algorithm)
Update : 2025-02-19 Size : 17.88mb Publisher : Nicke_zxl