[SDOI2008] 遞歸數列-實時
##題面一個由自然數組成的數列按下式定義:對于$i\lek$:$a_{i}=b_{i}
一個由自然數組成的數列按下式定義:
對于 \(i \le k\):\(a_{i}= b_{i}\)。
(資料圖片)
對于 \(i > k\):\(\displaystyle a_{i}= \sum_{j=1}^{k}{c_{j} \times a_{i-j}}\)。
其中 \(b_{1\dots k}\) 和 \(c_{1\dots k}\) 是給定的自然數。
寫一個程序,給定自然數 \(m \le n\),計算 \(\left( \sum_{i=m}^{n}{a_{i}} \right) \bmod p\)。
\(1 \le k \le 15\),\(1 \le m \le n \le 10^{18}\),\(0 \le b_{i},c_{i} \le 10^{9}\),\(p \le 10^{8}\)。
題解因為 \(k\) 很小,\(n, m\) 很大,不難想到矩陣加速遞推。
根據 \(\displaystyle a_{i}= \sum_{j=1}^{k}{c_{j} \times a_{i-j}}\),所以我們的矩陣應該至少是一個 \(1 \times k\) 的矩陣,可以列出初始矩陣:
\[\begin{bmatrix}a_k & a_{k - 1} & \cdots & a_2 & a_1\end{bmatrix}\]其下一個轉移則為:
\[\begin{bmatrix}a_{k + 1} & a_{k} & \cdots & a_3 & a_2\end{bmatrix}\]根據遞推式可以列出轉移矩陣:
\[\begin{bmatrix}c_1 & 1 & 0 & \cdots & 0\\c_2 & 0 & 1 & \cdots & 0\\\vdots & \vdots & \vdots & \ddots & 0\\c_n & 0 & 0 & \cdots & 1\end{bmatrix}\]這樣我們就可以在 \(\displaystyle \mathcal{O}(K^2logN)\) 的時間里遞推出 \(a_n\) 的值。但是我們回顧題意要求求出的值:
\[G(n, m) = \left( \sum_{i=m}^{n}{a_{i}} \right) \bmod p\]我們可以設 \(\displaystyle Sum(n) = \sum_{i = 1}^{n}a_i\) ,可以發現:
\[G(n, m) = Sum(n) - Sum(m - 1)\]所以我們可以在矩陣加速的時候一起處理出來 \(Sum(n)\),令我們的初始矩陣擴充為:
\[\begin{bmatrix}a_k & a_{k - 1} & \cdots & a_2 & a_1 & Sum(k - 1)\end{bmatrix}\]其下一個轉移則為:
\[\begin{bmatrix}a_{k + 1} & a_{k} & \cdots & a_3 & a_2 & Sum(k)\end{bmatrix}\]考慮到 \(Sum(n) = Sum(n - 1) + a_n\),可以得到擴充后的轉移矩陣為:
\[\begin{bmatrix}c_1 & 1 & 0 & \cdots & 0 & 1\\c_2 & 0 & 1 & \cdots & 0 & 0\\\vdots & \vdots & \vdots & \ddots & \vdots & \vdots\\c_{n - 1} & 0 & 0 & \cdots & 0 & 0\\c_n & 0 & 0 & \cdots & 1 & 1\end{bmatrix}\]這樣我們就可以在 \(\displaystyle \mathcal{O}(K^2logN)\) 的時間里解決這道題。
Code//Luogu - P2461#includetypedef long long valueType;typedef std::vector ValueVector;valueType MOD_;valueType const &MOD = MOD_;class Matrix {public: typedef long long valueType; typedef valueType &reference; typedef size_t sizeType; typedef std::vector Row; typedef std::vector Container; valueType MOD = ::MOD; enum TYPE : int { EMPTY = 0, UNIT = 1 };protected: sizeType _row_, _column_; Container data;public: Matrix(sizeType row, sizeType column) : _row_(row), _column_(column), data(_row_) { for (auto &iter: data) iter.resize(column, 0); }; sizeType row() const { return _row_; } sizeType column() const { return _column_; } void set(TYPE type) { for (auto &iter: data) { std::fill(iter.begin(), iter.end(), 0); } if (type == EMPTY) return; if (type == UNIT) for (sizeType i = 0, end = std::min(_row_, _column_); i < end; ++i) data[i][i] = 1; } reference operator()(sizeType i, sizeType j) { if (i > this->_row_ || j > this->_column_) throw std::out_of_range("Too Large."); if (i == 0 || j == 0) throw std::out_of_range("0 index access."); return std::ref(data[i - 1][j - 1]); } Matrix operator+(const Matrix &T) const { if (this->_row_ != T._row_ || this->_column_ != T._column_) throw std::range_error("Illegal operation."); Matrix result(this->_row_, this->_column_); for (sizeType i = 0; i < this->_row_; ++i) for (sizeType j = 0; j < this->_column_; ++j) result.data[i][j] = (this->data[i][j] + T.data[i][j]) % MOD; return result; } Matrix operator*(const Matrix &T) const { if (this->_column_ != T._row_) throw std::range_error("Illegal operation."); Matrix result(this->_row_, T._column_); for (sizeType i = 0; i < this->_row_; ++i) { for (sizeType k = 0; k < this->_column_; ++k) { valueType r = this->data[i][k]; for (sizeType j = 0; j < T._column_; ++j) result.data[i][j] = (result.data[i][j] + T.data[k][j] * r) % MOD; } } return result; } Matrix operator^(valueType x) const { if (x < 1) throw std::range_error("Illegal operation."); Matrix result(this->_row_, this->_column_); Matrix base = *this; result.set(UNIT); while (x) { if (x & 1) result = result * base; base = base * base; x = x >> 1; } return result; } friend std::ostream &operator<<(std::ostream &os, const Matrix &T) { for (sizeType i = 0; i < T._row_; ++i) for (sizeType j = 0; j < T._column_; ++j) os << T.data[i][j] << " \n"[j == T._column_ - 1]; return os; } friend std::istream &operator>>(std::istream &os, Matrix &T) { for (sizeType i = 0; i < T._row_; ++i) for (sizeType j = 0; j < T._column_; ++j) os >> T.data[i][j]; return os; }};int main() {valueType K, M, N;std::cin >> K;ValueVector B(K + 30, 0), C(K + 30, 0);for(int i = 1; i <= K; ++i)std::cin >> B[i];for(int i = 1; i <= K; ++i)std::cin >> C[i];std::cin >> M >> N >> MOD_;for(int i = 1; i <= K; ++i) {B[i] %= MOD;C[i] %= MOD;}Matrix ans(1, K + 1), base(K + 1, K + 1);ans.set(Matrix::EMPTY);base.set(Matrix::EMPTY);for(int i = 1; i <= K; ++i)base(i, 1) = C[i];for(int i = 2; i <= K; ++i)base(i - 1, i) = 1;base(1, K + 1) = base(K + 1, K + 1) = 1;for(int i = 1; i <= K; ++i)ans(1, K + 1 - i) = B[i];ans(1, K + 1) = std::accumulate(B.begin() + 1, B.begin() + K, 0) % MOD;valueType resultN = 0, resultM = 0;++N;if(N > K) {Matrix MatrixN = ans * (base ^ (N - K));resultN = MatrixN(1, K + 1);} else {resultN = std::accumulate(B.begin() + 1, B.begin() + N, 0);}if(M > K) {Matrix MatrixM = ans * (base ^ (M - K));resultM = MatrixM(1, K + 1);} else {resultM = std::accumulate(B.begin() + 1, B.begin() + M, 0);}valueType result = resultN - resultM;result = (result % MOD + MOD) % MOD;std::cout << result << std::flush;return 0;}