P123.38(sum)

#include<stdio.h>
int powers(int m,int n)
{
	int i,sum=1;
	for(i=1;i<=n;i++)
	{
		sum = sum*m;
	}
	return sum;
}
int sum_of_powers(int k,int n)
{
	int i,sum=0;
	for(i=1;i<=n;i++)
	{
		sum = sum + powers(i,k);
	}
	return sum;
}
int main()
{
	int p,q;
	while(1)
	{
		scanf("%d %d",&p,&q);
		printf("sum of %d powers of intergers from 1 to %d = %d\n",p,q,sum_of_powers(p,q));
	}
	return 0;
}

1.clc; 2.close all; 3.clear all; 4. 5.% 基本参数设置 6.Fs = 1e8; % 采样频率 7.Fj = 4e7; % 干扰带宽 8.T = 0.0001; % 时长 9.N = T * Fs; % 采样点数 10.f = linspace(‐Fs/2, Fs/2, N); % 频率范围 11.t = 0:1/Fs:T‐1/Fs; % 时间范围 12.Mfe = 10; % 有效调频指数 13.Fde = Fj / (2 * sqrt(2 * log(2))); % 有效调频带宽 14.Fn = Fde / Mfe; % 调制噪声带宽 15.fc = 1e6; 16. 17.% 参数改变范围 18.kf_values = [Mfe, Mfe*2]; 19.bw_factor_values = [1, 2]; 20.sigma_values = [1, 1]; 21. 22.% 初始化存储变量 23.P = zeros(1, N); 24.P_kf = zeros(1, N); 25.% 生成噪声调频信号并计算功率谱 26.for i = 1:100 27. N_white = randn(1, N); % 产生白噪声 28. F_N_white = fft(N_white); % 噪声频谱 29. window = fir1(N‐1, 2*Fn/Fs); % 产生N点的汉明窗,归一化频率为Fn/Fs 30. F_window = fft(window); % 窗函数频域 31. F_N_colored = F_window .* F_N_white; % 产生色噪声频谱 32. N_colored = ifft(F_N_colored); % 产生色噪声 33. sigma = std(N_colored); % 求色噪声方差 34. Mfe = Fde / sigma; 35. sn = zeros(1, N); 36. Sum1 = 0; 37. for k = 1:N‐1 38Sum1(k+1) = N_colored(k) + Sum1(k); % 平稳随机过程的积分 39. end 40. sn = Sum1 / Fs; 41. J = ones(1, N); 42. J = cos(2*pi*fc*t + Mfe*sn); % 产生噪声调频信号 43. F_J = fft(J); % 干扰信号的频谱 44. P1 = abs(F_J).^2; % 干扰信号功率谱 45. P = P + P1; 46.end 47.P = P / 100; 48.P = P / max(P); % 归一化 49.F_J = F_J / max(F_J); 50. 51.% 绘制原始信号图像 52.figure(1); 53.subplot(211); 54.plot(abs(F_N_white)); 55.title('噪声频谱'); 56.xlabel('频率/Hz'); 57.ylabel('幅度'); 58.subplot(212); 59.plot(abs(F_N_colored)); 60.title('噪声频谱加窗后'); 61.xlabel('频率/Hz'); 62.ylabel('幅度'); 63. 64.figure(2); 65.subplot(311); 66.plot(f, 10*log10(abs(fftshift(F_J)))); 67.title('调频干扰频域波形'); 68.xlabel('频率/Hz'); 69.ylabel('幅度/dB'); 70.subplot(312); 71.plot(f, 10*log10(abs(fftshift(P)))); 72.title('调频干扰功率谱'); 73.xlabel('频率/Hz'); 74.ylabel('幅度/dB'); 75.hold on 76.plot(f, ‐3, '‐g'); 77.subplot(313); 78.plot(t, J); 79.title('调频干扰时域波形'); 80.xlabel('时间/s'); 81.ylabel('幅度'); 82. 83.% 调频斜率对频谱的影响 84.figure; 85.hold on; 86.plot(f, 10*log10(abs(fftshift(P))), 'DisplayName', '原始'); % 绘制原始功 率谱 87.kf = kf_values(2); % 选择第二个值作为对比 88.P_kf = zeros(1, N); 89.for i = 1:100 90. N_white = randn(1, N); 91. F_N_white = fft(N_white); 92. window = fir1(N‐1, 2*Fn/Fs); 93. F_window = fft(window); 94. F_N_colored = F_window .* F_N_white; 95. N_colored = ifft(F_N_colored); 96. sigma = std(N_colored); 97. Mfe = Fde / sigma * kf / Mfe; % 调整调频斜率 98. sn = zeros(1, N); 99. Sum1 = 0; 100. for k = 1:N‐1 101. Sum1(k+1) = N_colored(k) + Sum1(k); 102. end 103. sn = Sum1 / Fs; 104. J = ones(1, N); 105. J = cos(2*pi + Mfe*sn); 106. F_J = fft(J); 107. P1 = abs(F_J).^2; 108. P_kf = P_kf + P1; 109.end 110.P_kf = P_kf / 100; 111.plot(f, 10*log10(abs(fftshift(P_kf))), 'DisplayName', ['kf = ', num2str(kf)]); 112.title('调频斜率下的调频干扰功率谱'); 113.xlabel('频率/Hz'); 114.ylabel('幅度/dB'); 115.legend; 116. 117.% 调制噪声带宽对频谱的影响 118.figure; 119.hold on; 120.plot(f, 10*log10(abs(fftshift(P))), 'DisplayName', '原始'); % 绘制原始 功率谱 121.bw_factor = bw_factor_values(2); % 选择第二个值作为对比 122.Fn_bw = Fn * bw_factor; 123.P_bw = zeros(1, N); 124.for i = 1:100 125. N_white = randn(1, N); 126. F_N_white = fft(N_white); 127. window = fir1(N‐1, 2*Fn_bw/Fs); % 调整带宽 128. F_window = fft(window); 129. F_N_colored = F_window .* F_N_white; 130. N_colored = ifft(F_N_colored); 131. sigma = std(N_colored); 132. Mfe = Fde / sigma; 133. sn = zeros(1, N); 134. Sum1 = 0; 135. for k = 1:N‐1 136. Sum1(k+1) = N_colored(k) + Sum1(k); 137. end 138. sn = Sum1 / Fs; 139. J = ones(1, N); 140. J = cos(2*pi + Mfe*sn); 141. F_J = fft(J); 142. P1 = abs(F_J).^2; 143. P_bw = P_bw + P1; 144.end 145.P_bw = P_bw / 100; 146.P_bw = P_bw / max(P_bw); % 归一化 147.plot(f, 10*log10(abs(fftshift(P_bw))), 'DisplayName', ['带宽因子 = ', num2str(bw_factor)]); 148.title('带宽因子下的调频干扰功率谱'); 149.xlabel('频率/Hz'); 150.ylabel('幅度/dB'); 151.legend; 152. 153.% 调制噪声功率对频谱的影响 154.figure; 155.hold on; 156.plot(f, 10*log10(abs(fftshift(P))), 'DisplayName', '原始'); % 绘制原始 功率谱 157.sigma = sigma_values(2); % 选择第二个值作为对比 158.P_sigma = zeros(1, N); 159.for i = 1:100 160. N_white = randn(1, N) * sigma; % 调整噪声功率 161. F_N_white = fft(N_white); 162. window = fir1(N‐1, 2*Fn/Fs); 163. F_window = fft(window); 164. F_N_colored = F_window .* F_N_white; 165. N_colored = ifft(F_N_colored); 166. Mfe = Fde / sigma; 167. sn = zeros(1, N); 168. Sum1 = 0; 169. for k = 1:N‐1 170. Sum1(k+1) = N_colored(k) + Sum1(k); 171. end 172. sn = Sum1 / Fs; 173. J = ones(1, N); 174. J = cos(2*pi + Mfe*sn); 175. F_J = fft(J); 176. P1 = abs(F_J).^2; 177. P_sigma = P_sigma + P1; 178.end 179.P_sigma = P_sigma / 100; 180.P_sigma = P_sigma / max(P_sigma); % 归一化 181.plot(f, 10*log10(abs(fftshift(P_sigma))), 'DisplayName', ['\sigma = ', num2str(sigma)]); 182.title('噪声功率下的调频干扰功率谱'); 183.xlabel('频率/Hz'); 184.ylabel('幅度/dB'); 185.legend; 帮我把这个matlab代码改成python可以吗
06-04
开始优化仿真... 总符号数: 32768 添加优化后的信道损伤... 应用改进的信号处理... 聚类错误: 'Start' 数组的第三维必须与 'replicates' 参数值匹配。 使用随机初始化代替... Starting parallel pool (parpool) using the 'Processes' profile ... iter phase num sum 1 1 32768 6505.77 2 1 3170 6005.05 3 1 1949 5821.25 4 1 1590 5717.79 5 1 1084 5671.11 6 1 703 5651.21 7 1 481 5642.85 8 1 320 5638.8 9 1 245 5636.61 10 1 206 5635.08 11 1 170 5633.97 12 1 146 5633.19 13 1 117 5632.61 14 1 108 5632.14 15 1 117 5631.66 16 1 112 5631.16 17 1 121 5630.59 18 1 128 5630 19 1 129 5629.45 20 1 133 5628.86 21 1 131 5628.25 22 1 119 5627.73 23 1 115 5627.27 24 1 115 5626.81 25 1 91 5626.44 26 1 92 5626.12 27 1 77 5625.85 28 1 85 5625.6 29 1 69 5625.41 30 1 59 5625.25 31 1 56 5625.13 32 1 57 5625.01 33 1 54 5624.88 34 1 60 5624.73 35 1 64 5624.55 36 1 62 5624.36 37 1 62 5624.17 38 1 62 5624 39 1 57 5623.84 40 1 68 5623.66 41 1 54 5623.51 42 1 63 5623.33 43 1 73 5623.11 44 1 61 5622.95 45 1 41 5622.86 46 1 36 5622.79 47 1 49 5622.7 48 1 55 5622.58 49 1 49 5622.46 50 1 69 5622.29 51 1 59 5622.14 52 1 54 5622.02 53 1 61 5621.86 54 1 59 5621.7 55 1 60 5621.53 56 1 61 5621.32 57 1 60 5621.15 58 1 57 5620.99 59 1 55 5620.83 60 1 67 5620.63 61 1 55 5620.44 62 1 63 5620.27 63 1 62 5620.1 64 1 46 5619.98 65 1 36 5619.94 66 1 22 5619.92 67 1 18 5619.9 68 1 16 5619.88 69 1 16 5619.87 70 1 16 5619.85 71 1 11 5619.85 72 1 12 5619.84 73 1 11 5619.83 74 1 10 5619.83 75 1 17 5619.81 76 1 17 5619.79 77 1 17 5619.78 78 1 17 5619.76 79 1 23 5619.74 80 1 31 5619.68 81 1 36 5619.61 82 1 39 5619.55 83 1 25 5619.5 84 1 31 5619.46 85 1 23 5619.44 86 1 13 5619.44 87 1 12 5619.42 88 1 11 5619.42 89 1 11 5619.41 90 1 11 5619.41 91 1 4 5619.4 92 1 1 5619.4 93 1 1 5619.4 1 1 32768 7016.92 2 1 4292 6385.06 3 1 2484 6132.63 4 1 2074 5941.22 5 1 1880 5798.36 6 1 1418 5717.98 7 1 958 5683.89 8 1 652 5668.93 9 1 441 5661.99 10 1 321 5658.28 11 1 230 5656.38 12 1 224 5654.78 13 1 216 5653.19 14 1 182 5651.7 15 1 190 5650.12 16 1 186 5648.6 17 1 175 5647.09 18 1 169 5645.9 19 1 164 5644.7 20 1 167 5643.45 21 1 132 5642.47 22 1 117 5641.79 23 1 122 5641.06 24 1 147 5640.06 25 1 142 5639.04 26 1 129 5638.27 27 1 132 5637.47 28 1 140 5636.49 29 1 153 5635.34 30 1 141 5634.27 31 1 154 5633.14 32 1 141 5632.12 33 1 129 5631.15 34 1 136 5630.27 35 1 138 5629.37 36 1 133 5628.57 37 1 122 5627.83 38 1 126 5627.11 39 1 121 5626.45 40 1 104 5625.92 41 1 88 5625.53 42 1 92 5625.21 43 1 81 5624.88 44 1 78 5624.57 45 1 73 5624.3 46 1 76 5624.04 47 1 73 5623.75 48 1 70 5623.54 49 1 66 5623.34 50 1 72 5623.11 51 1 59 5622.91 52 1 60 5622.74 53 1 67 5622.52 54 1 62 5622.32 55 1 74 5622.11 56 1 62 5621.91 57 1 66 5621.69 58 1 71 5621.45 59 1 72 5621.23 60 1 67 5621.03 61 1 77 5620.74 62 1 79 5620.46 63 1 76 5620.19 64 1 67 5619.97 65 1 61 5619.82 66 1 43 5619.72 67 1 43 5619.66 68 1 30 5619.61 69 1 24 5619.57 70 1 24 5619.54 71 1 25 5619.51 72 1 22 5619.49 73 1 24 5619.45 74 1 18 5619.43 75 1 18 5619.42 76 1 14 5619.4 77 1 15 5619.39 78 1 17 5619.38 79 1 18 5619.37 80 1 17 5619.36 81 1 5 5619.36 82 1 7 5619.35 83 1 4 5619.35 84 1 5 5619.35 85 1 6 5619.35 86 1 9 5619.35 87 1 3 5619.34 88 1 2 5619.34 1 1 32768 8512.25 2 1 5675 7087.36 3 1 3814 6570.26 4 1 2111 6449.26 5 1 998 6424.8 6 1 485 6416.99 7 1 378 6411.11 8 1 482 6400.75 9 1 729 6376.52 10 1 1023 6326.41 11 1 1407 6225.36 12 1 1827 6068.49 13 1 1938 5900.86 14 1 1640 5785.47 15 1 1201 5732.06 16 1 813 5709.38 17 1 534 5700.26 18 1 357 5696.2 19 1 233 5694.32 20 1 176 5693.2 21 1 133 5692.54 22 1 99 5692.17 23 1 81 5691.94 24 1 59 5691.78 25 1 59 5691.64 26 1 48 5691.54 27 1 37 5691.48 28 1 30 5691.45 29 1 22 5691.43 30 1 18 5691.41 31 1 16 5691.4 32 1 21 5691.37 33 1 21 5691.35 34 1 28 5691.31 35 1 33 5691.26 36 1 37 5691.22 37 1 28 5691.15 38 1 32 5691.1 39 1 36 5691.03 40 1 37 5690.97 41 1 48 5690.86 42 1 59 5690.69 43 1 49 5690.54 44 1 52 5690.39 45 1 57 5690.22 46 1 60 5690.03 47 1 69 5689.84 48 1 86 5689.57 49 1 85 5689.29 50 1 66 5689.07 51 1 67 5688.87 52 1 72 5688.65 53 1 54 5688.48 54 1 71 5688.26 55 1 71 5688.05 56 1 60 5687.89 57 1 58 5687.74 58 1 55 5687.58 59 1 51 5687.44 60 1 55 5687.29 61 1 50 5687.14 62 1 56 5686.99 63 1 60 5686.82 64 1 61 5686.6 65 1 62 5686.39 66 1 67 5686.2 67 1 69 5685.98 68 1 71 5685.72 69 1 73 5685.46 70 1 63 5685.26 71 1 56 5685.12 72 1 60 5684.97 73 1 56 5684.81 74 1 69 5684.62 75 1 64 5684.4 76 1 71 5684.15 77 1 85 5683.83 78 1 98 5683.4 79 1 85 5683.1 80 1 62 5682.85 81 1 73 5682.63 82 1 74 5682.41 83 1 70 5682.17 84 1 71 5681.94 85 1 84 5681.65 86 1 79 5681.33 87 1 90 5681.04 88 1 101 5680.67 89 1 88 5680.33 90 1 82 5680.02 91 1 95 5679.71 92 1 103 5679.26 93 1 107 5678.77 94 1 118 5678.16 95 1 109 5677.56 96 1 124 5676.86 97 1 134 5676.11 98 1 108 5675.55 99 1 130 5674.86 100 1 118 5674.26 101 1 99 5673.78 102 1 99 5673.33 103 1 95 5672.8 104 1 112 5672.24 105 1 101 5671.83 106 1 98 5671.46 107 1 76 5671.16 108 1 69 5670.95 109 1 74 5670.7 110 1 66 5670.5 111 1 79 5670.25 112 1 78 5669.97 113 1 70 5669.77 114 1 66 5669.59 115 1 62 5669.43 116 1 64 5669.25 117 1 73 5669.03 118 1 75 5668.79 119 1 63 5668.61 120 1 48 5668.5 121 1 46 5668.4 122 1 34 5668.33 123 1 29 5668.3 124 1 23 5668.28 125 1 25 5668.25 126 1 26 5668.21 127 1 32 5668.15 128 1 32 5668.1 129 1 32 5668.04 130 1 32 5667.99 131 1 23 5667.95 132 1 18 5667.92 133 1 19 5667.9 134 1 12 5667.9 135 1 12 5667.89 136 1 9 5667.89 137 1 2 5667.89 138 1 1 5667.89 139 1 2 5667.89 140 1 3 5667.89 141 1 2 5667.89 1 1 32768 5795.51 2 1 1800 5670.03 3 1 857 5643.7 4 1 558 5632.33 5 1 358 5627.49 6 1 232 5625.35 7 1 200 5623.94 8 1 157 5622.99 9 1 114 5622.47 10 1 100 5622.09 11 1 80 5621.82 12 1 78 5621.59 13 1 65 5621.42 14 1 68 5621.22 15 1 65 5621.03 16 1 58 5620.87 17 1 68 5620.69 18 1 64 5620.5 19 1 66 5620.31 20 1 52 5620.16 21 1 52 5620.03 22 1 38 5619.96 23 1 22 5619.94 24 1 21 5619.92 25 1 20 5619.89 26 1 20 5619.87 27 1 21 5619.86 28 1 11 5619.85 29 1 10 5619.84 30 1 14 5619.84 31 1 10 5619.83 32 1 17 5619.82 33 1 15 5619.8 34 1 17 5619.78 35 1 15 5619.76 36 1 21 5619.74 37 1 30 5619.7 38 1 38 5619.62 39 1 34 5619.56 40 1 34 5619.51 41 1 30 5619.47 42 1 26 5619.44 43 1 13 5619.44 44 1 12 5619.42 45 1 11 5619.42 46 1 11 5619.41 47 1 11 5619.41 48 1 4 5619.4 49 1 1 5619.4 50 1 1 5619.4 1 1 32768 6153.1 2 1 2887 5821.24 3 1 1436 5740.66 4 1 973 5707.13 5 1 629 5692.83 6 1 419 5686.56 7 1 322 5682.35 8 1 271 5679.45 9 1 188 5677.52 10 1 157 5676.45 11 1 134 5675.76 12 1 132 5675.06 13 1 120 5674.47 14 1 129 5673.82 15 1 139 5673.11 16 1 116 5672.56 17 1 105 5672.02 18 1 102 5671.59 19 1 92 5671.22 20 1 100 5670.83 21 1 96 5670.34 22 1 86 5669.95 23 1 90 5669.67 24 1 66 5669.45 25 1 64 5669.25 26 1 61 5669.08 27 1 62 5668.9 28 1 60 5668.74 29 1 50 5668.61 30 1 58 5668.48 31 1 43 5668.4 32 1 39 5668.33 33 1 24 5668.29 34 1 22 5668.26 35 1 26 5668.22 36 1 29 5668.18 37 1 29 5668.13 38 1 33 5668.07 39 1 28 5668.02 40 1 26 5667.98 41 1 22 5667.94 42 1 21 5667.91 43 1 13 5667.9 44 1 12 5667.9 45 1 11 5667.89 46 1 8 5667.89 47 1 2 5667.89 48 1 1 5667.89 49 1 2 5667.89 50 1 3 5667.89 51 1 2 5667.89 距离的最佳总和 = 5619.34 生成增强的性能分析图表... 优化后的系统性能指标: 误码率(BER): 4.50e-01 星座图清晰度指数(CQI): 2.7234 聚类中心平均偏移: X:0.4103, Y:1.0267 优化仿真完成! Parallel pool using the 'Processes' profile is shutting down. This parallel pool has been shut down. 原因: The parallel pool shut down because the client lost connection to worker 8. Check the network connection or restart the parallel pool with 'parpool'.
06-19
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