In addition to the weights of synaptic shared connections, PNN includes weights of synaptic effective ranges [14-24]. PNN considers synaptic strength balance in dynamic of phagocytosing of synapses and static of constant sum of synapses length [14], and includes the lead behavior of the school of fish. Synapse formation will inhibit dendrites generation to a certain extent in experiments and PNN simulations [15]. The memory persistence gradient of retrograde circuit similar to the Enforcing Resilience in a Spring Boot. The relatively good and inferior gradient information stored in memory engram cells in synapse formation of retrograde circuit like the folds of the brain [16]. The controversy was claimed if human hippocampal neurogenesis persists throughout aging, PNN considered it may have a new and longer circuit in late iteration [17,18]. Closing the critical period will cause neurological disorder in experiments and PNN simulations [19]. Considering both negative and positive memories persistence help activate synapse length changes with iterations better than only considering positive memory [20]. Astrocytic phagocytosis will avoid the local accumulation of synapses by simulation, Lack of astrocytic phagocytosis causes excitatory synapses and functionally impaired synapses accumulate in experiments and lead to destruction of cognition, but local longer synapses and worse results in PNN simulations [21]. It gives relationship of intelligence and cortical thickness, individual differences in brain [22]. The PNN also considered the memory engram cells that strengthened Synaptic strength [23]. The effects of PNN's memory structure and tPBM may be the same for powerful penetrability of signals [24]. Memory persistence also inhibit local synaptic accumulation. By PNN, it may introduce the relatively good and inferior solution in PSO. The simple PNN only has the synaptic phagocytosis.
翻译:除了突触共有连接的重量外, PNN 还将包括超声速共享连接的重量, PNN 还包括超音速有效范围[14-24] 的重量。 PNN 考虑超音速突触和恒定突触长度总和的静态[14] 的动态中超音速强度的平衡。 超音速形成将在某种程度上抑制衰变的生成, 实验和 PNN 模拟[15] 。 类似于 Spring Boot 中超音速恢复力的回溯电路的记忆持续度梯度梯度梯度梯度梯度。 存储于脑积细胞中的相对良好和低调梯度信息, 像大脑的折叠合器一样。 如果人类的时速突变神经元变化在生长过程中持续发生, PNNNP 认为它可能有一个新的和更长的回路路程。 关闭关键时期只会在实验和PNNEM 模拟中造成神经紊变变变变,但考虑到负和积极的内振变变变的内变变变, 。 将使得内核的内核的内变变变的内变变变变变变变变的机的内变的内变变的内变变变变的机结构结构会更会变。