AM PM

1. 24-hour clock system

00:00:00 - 23:59:59

2. 12-hour clock system

12:00:00 am - 11:59:59 am

12:00:00 pm - 11:59:59 pm

no 00:00 am or 00:00 pm, it should be 12 midnight or 12 noon



It is incorrect to write 0:00p.m. The use of 0:00 implies a 24-hour clock system, while the use of A.M. and P.M. implies a 12-hour clock system. Therefore, it is absolutely wrong to use both together.

The 12-hour clock divides the day into two parts, 12 hours each. The middle of the day (midday) is the twelfth hour, noon, or the meridiem. A.M. refers to the hours prior to midday (Latin: ante meridiem) while P.M. refers to the hours after midday (Latin: post meridiem). Since the meridien is thought to occur right at the exact second of the 12th and 24th hours, it is most common to hear the times referred to as 12 noon or 12 midnight, rather than using a.m. or p.m. However, to be clear, 12:01p.m. refers to the time just after (post) the 12th hour, that is, the first minute after midday (noon); while 12:01a.m. refers to the first minute of the new day, therefore prior to (ante) midday, that is, just after midnight (after the 24th hour of the previous day).


The 24-hour clock does not need a reference to the middle of the day, the meridiem, which is why the suffix a.m. or p.m. used with this system is completely unnecessary, incorrect, and confusing. So you are wrong to say that “Okay, 0:01AM means something”. It actually doesn’t mean anything at all for the reasons I have given. 0:01 as written implies the 24-hour clock (although it would probably be written 00:01 instead). It refers to the start of the new day. The equivalent in the 12-hour clock would be 12:01 midnight (or 12:01a.m.). 


So if your friends ask you to meet up at 12:00a.m., it should be very clear to you by now that you would be left standing all alone and feeling silly if you showed up at midday, noon, 12:01 p.m., the 12th hour… They are asking you to show up at the first hour of the day, which is just after (or right at) midnight.
考虑柔性负荷的综合能源系统低碳经济优化调度【考虑碳交易机制】(Matlab代码实现)内容概要:本文围绕“考虑柔性负荷的综合能源系统低碳经济优化调度”展开,重点研究在碳交易机制下如何实现综合能源系统的低碳化与经济性协同优化。通过构建包含风电、光伏、储能、柔性负荷等多种能源形式的系统模型,结合碳交易成本与能源调度成本,提出优化调度策略,以降低碳排放并提升系统运行经济性。文中采用Matlab进行仿真代码实现,验证了所提模型在平衡能源供需、平抑可再生能源波动、引导柔性负荷参与调度等方面的有效性,为低碳能源系统的设计与运行提供了技术支撑。; 适合人群:具备一定电力系统、能源系统背景,熟悉Matlab编程,从事能源优化、低碳调度、综合能源系统等相关领域研究的研究生、科研人员及工程技术人员。; 使用场景及目标:①研究碳交易机制对综合能源系统调度决策的影响;②实现柔性负荷在削峰填谷、促进可再生能源消纳中的作用;③掌握基于Matlab的能源系统建模与优化求解方法;④为实际综合能源项目提供低碳经济调度方案参考。; 阅读建议:建议读者结合Matlab代码深入理解模型构建与求解过程,重点关注目标函数设计、约束条件设置及碳交易成本的量化方式,可进一步扩展至多能互补、需求响应等场景进行二次开发与仿真验证。
### AMPM、FM频谱分析及信号处理 #### 振幅调制(AM)频谱分析 振幅调制(AM)的频谱包括三个主要部分:载波频率 \( f_c \)、上边带(USB, \( f_c + f_m \))和下边带(LSB, \( f_c - f_m \))。信息信号的高频成分位于上边带,而低频成分则位于下边带。AM的优点在于实现简单且硬件成本低,因此广泛应用于早期广播系统如AM收音机[^1]。然而,AM也存在效率低的问题,因为载波本身不携带信息,并且上下边带冗余。此外,AM容易受到噪声干扰,抗噪性较差。 #### 频率调制(FM)频谱分析 在频率调制(FM)中,基带信号被用于调制载波信号的频率,使得载波频率随基带信号的变化而变化。FM调制产生一个带宽较宽的调制信号,其中包含无限多个边带。随着已调制信号的幅值增大,其频谱变得更加分散,边带包含更多的频率,并以载波频率 \( f_0 \) 为中心对称分布。例如,当中心频率为 \( f_0 = 11.97 \, \text{Hz} \),频率偏移为 \( \Delta f = 0.3861 \, \text{Hz} \) 时,频谱能量逐渐向两边扩展,且载波频率不再是幅值最高的频率[^2]。这种特性使得FM具有更高的抗噪性和更高质量的信号传输能力[^3]。 #### 相位调制(PM)频谱分析 相位调制(PM)与频率调制类似,但它是通过改变载波信号的相位来传输基带信号。PM的频谱结构与FM相似,同样包含无限多个边带,并以载波频率为中心对称分布。PM的频谱特性取决于调制指数,调制指数越大,频谱越分散,边带数量越多。尽管PM和FM在频谱结构上有相似之处,但PM对相位变化更为敏感,因此在某些应用中需要更精确的相位控制。 #### 信号处理中的AMPM、FM频谱分析 在信号处理中,AMPM和FM的频谱分析是理解调制信号特性的关键。通过对频谱的分析,可以评估信号的质量、带宽需求以及抗噪性能。例如,在AM信号中,可以通过滤波器去除不必要的边带以提高效率;在FM信号中,可以通过增加带宽来提高抗噪性能;而在PM信号中,可以通过调整调制指数来优化频谱分布。 ```python import numpy as np import matplotlib.pyplot as plt # 示例代码:生成AM、FM、PM信号并绘制频谱 fs = 1000 # 采样频率 t = np.linspace(0, 1, fs) # 时间向量 fc = 50 # 载波频率 fm = 5 # 基带信号频率 A = 1 # 载波振幅 k_am = 0.5 # AM调制指数 k_fm = 10 # FM调制指数 k_pm = 1 # PM调制指数 # 基带信号 m_t = np.sin(2 * np.pi * fm * t) # AM信号 am_signal = (1 + k_am * m_t) * np.cos(2 * np.pi * fc * t) # FM信号 fm_signal = np.cos(2 * np.pi * fc * t + k_fm * np.cumsum(m_t)) # PM信号 pm_signal = np.cos(2 * np.pi * fc * t + k_pm * m_t) # 绘制频谱 plt.figure(figsize=(12, 8)) plt.subplot(3, 1, 1) plt.magnitude_spectrum(am_signal, Fs=fs, color='b') plt.title('AM Signal Spectrum') plt.subplot(3, 1, 2) plt.magnitude_spectrum(fm_signal, Fs=fs, color='g') plt.title('FM Signal Spectrum') plt.subplot(3, 1, 3) plt.magnitude_spectrum(pm_signal, Fs=fs, color='r') plt.title('PM Signal Spectrum') plt.tight_layout() plt.show() ```
评论
成就一亿技术人!
拼手气红包6.0元
还能输入1000个字符
 
红包 添加红包
表情包 插入表情
 条评论被折叠 查看
添加红包

请填写红包祝福语或标题

红包个数最小为10个

红包金额最低5元

当前余额3.43前往充值 >
需支付:10.00
成就一亿技术人!
领取后你会自动成为博主和红包主的粉丝 规则
hope_wisdom
发出的红包
实付
使用余额支付
点击重新获取
扫码支付
钱包余额 0

抵扣说明:

1.余额是钱包充值的虚拟货币,按照1:1的比例进行支付金额的抵扣。
2.余额无法直接购买下载,可以购买VIP、付费专栏及课程。

余额充值