mizunototori

,

mizunototori

def is_prime(n):
# nが素数かどうか判定するプログラム
    for p in range(2, int(math.sqrt(n)) + 1):
        if n % p == 0:
            return False # 素数でないならFalseを返す
    return True # 素数ならTrueを返す

def get_prime(str_num, N):
# 文字列として受け取ったstr_numからN桁の最初の素数を見つけるプログラム
    for i in range(0, len(str_num) - N):

mizunototori

.CodeMirror pre {
    font-family: Consolas;
    font-size: 12pt;
}

.output_subarea.output_text.output_stream.output_stdout,
.output_subarea.output_text pre {
    font-family: Consolas;
    font-size: 12pt;
}

mizunototori

def _make_nn_sparse_coded_signal(n_samples, n_components, n_features,
                                 n_nonzero_coefs, random_state=None):
    """Generate a signal as a sparse combination of dictionary elements.
    Returns a matrix Y = DX, such as D is (n_features, n_components),
    X is (n_components, n_samples) and each column of X has exactly
    n_nonzero_coefs non-zero elements.
    Read more in the :ref:`User Guide <sample_generators>`.
    Parameters
    ----------

mizunototori

mizunototori

function [Dictionary, data, coefs] = gererateSyntheticDictionaryAndData(N, L, dim, K, SNRdB)
%% Returns dictionary, a data matrix and a coefficient matrix

%      		Data 		= 		Dictionary 		x 	Coefficient matrix
%      _____ ... _____      _________________       _____ ... ______ 
%     |               |    |				 |     |				| 
%     |               |    |				 |     |				| 
%     |               | =  |				 |  x  |				| 
%     |               |    |				 |     |				| 
%     |               |    |				 |     |				| 

mizunototori

def _make_nn_sparse_coded_signal(n_samples, n_components, n_features,
                                 n_nonzero_coefs, random_state=None):
    """Generate a signal as a sparse combination of dictionary elements.
    Returns a matrix Y = DX, such as D is (n_features, n_components),
    X is (n_components, n_samples) and each column of X has exactly
    n_nonzero_coefs non-zero elements.
    Read more in the :ref:`User Guide <sample_generators>`.
    Parameters
    ----------
    n_samples : int

mizunototori

function [Dictionary, data, coefs] = gererateSyntheticDictionaryAndData(N, L, dim, K, SNRdB)
%% Returns dictionary, a data matrix and a coefficient matrix

%      		Data 		= 		Dictionary 		x 	Coefficient matrix
%      _____ ... _____      _________________       _____ ... ______ 
%     |               |    |				 |     |				| 
%     |               |    |				 |     |				| 
%     |               | =  |				 |  x  |				| 
%     |               |    |				 |     |				| 
%     |               |    |				 |     |				| 

mizunototori

>> file_name = 'ファイルのある場所/random_mat.mat';
>> file_data = load(file_name);
>> data = file_data.data;
[U S V flag] = svds((data), 1); % SVDのサブセット, 最大特異値の出力を得る

>> U'

  1 列から 12 列
    0.2245    0.2040    0.2040    0.2177    0.2319    0.2341    0.2295    0.2020    0.1833    0.2041    0.2266    0.2597
  13 列から 20 列

mizunototori