This article employs a combined approach of biology and economics to reveal that biological evolution has an economic nature, evolving towards improved energy efficiency. The orthodox Darwinian theory of evolution des...This article employs a combined approach of biology and economics to reveal that biological evolution has an economic nature, evolving towards improved energy efficiency. The orthodox Darwinian theory of evolution describes evolution as the random variation of organisms and their survival through natural selection. In fact, the natural environment itself is a constantly changing context, and the strategy to adapt to this change is to enhance behavioral capabilities, thereby expanding the range and dimensions of behavior. Therefore, the improvement of behavioral capabilities is an important aspect of evolution. The enhancement of behavioral capabilities expands the range of adaptation to the natural environment and increases the space for behavioral choices. Within this space of behavioral choices, some options are more effective and superior to others;thus, the ability to select is necessary to make the improved behavioral capabilities more beneficial to the organism itself. The birth and development of the brain serve the purpose of selection. By using the brain to make selections, at least the “better” behavior will be chosen between two alternatives. Once the better behavior yields better results, and the organism can associate these results with the corresponding behavior, it will persist in this behavior. The persistent repetition of a behavior over generations will form a habit. Habits passed down through generations constitute a new environment, causing the organism’s genes to activate or deactivate certain functions, ultimately leading to genetic changes that are beneficial to that habit. Since the brain’s selection represents the organism’s self-selection, it differs from random variation;it is also a rational selection, choosing behaviors that either obtain more energy or reduce energy consumption. Thus, this evolution possesses an economic nature.展开更多
在正交频分复用(orthogonal frequency division multiplexing,OFDM)波形外辐射源雷达系统中,相对于直达波和多径回波,目标回波的功率要微弱许多,因此多径杂波抑制是此雷达信号处理的一项关键技术。许多时域自适应滤波算法被用来抑制直...在正交频分复用(orthogonal frequency division multiplexing,OFDM)波形外辐射源雷达系统中,相对于直达波和多径回波,目标回波的功率要微弱许多,因此多径杂波抑制是此雷达信号处理的一项关键技术。许多时域自适应滤波算法被用来抑制直达波和多径回波,但往往存在滤波器阶数过多,或计算负担过高的问题。基于OFDM波形的多载波调制特性,提出了分载波自适应滤波算法,相比于常规时域自适应滤波算法,能够有效降低滤波器阶数和计算复杂度,简单且高效。以基于OFDM调制原理的数字调幅广播外辐射源雷达为例,详细介绍了分载波递归最小二乘和分载波归一化最小均方算法的自适应滤波原理和过程,并基于仿真和实测数据分析比较了常规时域自适应滤波算法和分载波自适应滤波算法的性能差异。展开更多
互补序列集(Complementary Sets of Sequences,CSS)具备良好的自相关性能,但在频谱受限的条件下,自相关性能恶化,因此有必要对频谱受限的CSS,即互补稀疏频率(Complementary Sparse Frequency,CSF)序列集,进行优化设计。本文以加权积分...互补序列集(Complementary Sets of Sequences,CSS)具备良好的自相关性能,但在频谱受限的条件下,自相关性能恶化,因此有必要对频谱受限的CSS,即互补稀疏频率(Complementary Sparse Frequency,CSF)序列集,进行优化设计。本文以加权积分旁瓣电平(Weighted Integral Sidelobe Level,WISL)表征序列集的自相关性能,以频率阻带内的能量(Energy in the Frequency Stopband,EFS)表征序列集的稀疏频谱性能;并将二者的加权和作为目标函数,以序列集为优化变量,在恒模的约束下,建立联合优化问题。针对该优化问题,采用循环迭代算法(Cyclic Iterative Algorithm,CIA)求解,引入辅助变量,将辅助变量和序列集变量迭代求解。由于在每次迭代过程中都可求得序列集的恒模闭式解,相比于其他的CSF序列集优化算法,CIA收敛速度快,所设计CSF序列集的相关特性和频谱特性好,且可抑制指定范围内的自相关旁瓣。仿真结果验证了所提算法的有效性和优异性。展开更多
文摘This article employs a combined approach of biology and economics to reveal that biological evolution has an economic nature, evolving towards improved energy efficiency. The orthodox Darwinian theory of evolution describes evolution as the random variation of organisms and their survival through natural selection. In fact, the natural environment itself is a constantly changing context, and the strategy to adapt to this change is to enhance behavioral capabilities, thereby expanding the range and dimensions of behavior. Therefore, the improvement of behavioral capabilities is an important aspect of evolution. The enhancement of behavioral capabilities expands the range of adaptation to the natural environment and increases the space for behavioral choices. Within this space of behavioral choices, some options are more effective and superior to others;thus, the ability to select is necessary to make the improved behavioral capabilities more beneficial to the organism itself. The birth and development of the brain serve the purpose of selection. By using the brain to make selections, at least the “better” behavior will be chosen between two alternatives. Once the better behavior yields better results, and the organism can associate these results with the corresponding behavior, it will persist in this behavior. The persistent repetition of a behavior over generations will form a habit. Habits passed down through generations constitute a new environment, causing the organism’s genes to activate or deactivate certain functions, ultimately leading to genetic changes that are beneficial to that habit. Since the brain’s selection represents the organism’s self-selection, it differs from random variation;it is also a rational selection, choosing behaviors that either obtain more energy or reduce energy consumption. Thus, this evolution possesses an economic nature.
文摘在正交频分复用(orthogonal frequency division multiplexing,OFDM)波形外辐射源雷达系统中,相对于直达波和多径回波,目标回波的功率要微弱许多,因此多径杂波抑制是此雷达信号处理的一项关键技术。许多时域自适应滤波算法被用来抑制直达波和多径回波,但往往存在滤波器阶数过多,或计算负担过高的问题。基于OFDM波形的多载波调制特性,提出了分载波自适应滤波算法,相比于常规时域自适应滤波算法,能够有效降低滤波器阶数和计算复杂度,简单且高效。以基于OFDM调制原理的数字调幅广播外辐射源雷达为例,详细介绍了分载波递归最小二乘和分载波归一化最小均方算法的自适应滤波原理和过程,并基于仿真和实测数据分析比较了常规时域自适应滤波算法和分载波自适应滤波算法的性能差异。
文摘互补序列集(Complementary Sets of Sequences,CSS)具备良好的自相关性能,但在频谱受限的条件下,自相关性能恶化,因此有必要对频谱受限的CSS,即互补稀疏频率(Complementary Sparse Frequency,CSF)序列集,进行优化设计。本文以加权积分旁瓣电平(Weighted Integral Sidelobe Level,WISL)表征序列集的自相关性能,以频率阻带内的能量(Energy in the Frequency Stopband,EFS)表征序列集的稀疏频谱性能;并将二者的加权和作为目标函数,以序列集为优化变量,在恒模的约束下,建立联合优化问题。针对该优化问题,采用循环迭代算法(Cyclic Iterative Algorithm,CIA)求解,引入辅助变量,将辅助变量和序列集变量迭代求解。由于在每次迭代过程中都可求得序列集的恒模闭式解,相比于其他的CSF序列集优化算法,CIA收敛速度快,所设计CSF序列集的相关特性和频谱特性好,且可抑制指定范围内的自相关旁瓣。仿真结果验证了所提算法的有效性和优异性。
