2) normalized min-sum algorithm 归一化最小和算法3) NLMS 归一化最小均方 1. Normalized least mean square(NLMS)adapting filtering technology has been applieread spectrum c mmunication system to lim t narrowband interferences in the situationd tosp o i of Gaun ises. 为了提高直扩通信系统在...
Normalized Min-Sum algorithmiterative decodingIn this letter an improvement is proposed for the Normalized Min-Sum (NMS) algorithm to decode LowDensity Parity Check codes. The new algorithm introduces an efficient adjustment for check node update in view of several common error conditions in decoding...
2) layered revised min-sum decoding algorithm 分层修正最小和译码算法 1. And a new layered revised min-sum decoding algorithm is proposed,then fixed-point simulation result shows that this algorithm can improve decoding throughout and reduce iteration. 提出了分层修正最小和译码算法并对该算法进行...
RMSE 是预测值和真实值之间差异的平方和的均方根值,用来衡量预测值和真实值之间的平均误差。如果有 n 个观测值,预测值为 ŷi,真实值为 yi,则 RMSE 可以计算为: RMSE = sqrt(1/n * sum((yi - ŷi)^2)) 其中,sqrt 表示开方,sum 表示求和。 Normalized RMSE 将 RMSE 进行归一化处理,可以使得不...
Other Current Assets - Field containing the sum of all current assets that cannot be standardized into another field as well as those that are aggregated by the company because materially, they are too small to list separately. Diluted EPS Incl Extra Items - Company's net earnings or losses ...
MPSNNReduceFeatureChannelsAndWeightsSum MPSNNReduceFeatureChannelsArgumentMax MPSNNReduceFeatureChannelsArgumentMin MPSNNReduceFeatureChannelsMax MPSNNReduceFeatureChannelsMean MPSNNReduceFeatureChannelsMin MPSNNReduceFeatureChannelsSum MPSNNReduceRowMax MPSNNReduceRowMean MPSNNReduceRowMin MPSNNReduceRo...
res = min(res, H_Xi_given_Yj(Xi, Y[i])); } return res; } //H(Xi|Y)_norm double H_Xi_given_Y_norm(vector & Xi, vector<vector > & Y) { return H_Xi_given_Y(Xi, Y) / H(Xi); } //H(X|Y) = sum {H(Xi|Y)} double H_X_given_Y(vector<vector > & X, vector<...
C. MIN D. SUM 查看完整题目与答案 配对资料的两个样本是相互独立的关系。 A. 正确 B. 错误 查看完整题目与答案 误区:__是我国社会主义经济制度的基础。改正:公有制经济。 查看完整题目与答案 离断肢体应快速转运,并力争尽早进行手术的吋机是 A. 6小时内 B. 7小时内 C. 8小时内 ...
\[y^TDy = \sum_{x_i > 0}d_i + b^2 \sum_{x_i < 0}d_i = b( \sum_{x_i < 0}d_i + b \sum_{x_i < 0}d_i) = b1^TD1. \] \[4 \cdot Ncut(A, B) = \frac{y^T(D-W)y}{y^TDy}. \] 故 \[\min_x Ncut(A, B) = \min_y \frac{1}{4} \frac{y^T(...
imagesc() does (data-min)/(max-min) but your manual conversion does data/max