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migarney information theory

2023-03-01 14:58 作者:migarney  | 我要投稿

Hi researcher ,

it can have many frequency communication with similar and allowing and alternative and so on to a lot of visual?neuro module for become many dynamic combinations through inducing to frequency modulation and the same frequency to syntony.and then having many?jointing to the frequency of?visible spectrum to become the?visual imaging by the mutation function of migarney information theory ,and it need not having the?trainning to the?visual cortex by the deep neuro network . because it is very slowing about the speed of trainning?to the?visual cortex by the deep neuro network.the fastest of speed is that the speed of?having many?jointing to the frequency of?visible spectrum to become the?visual imaging by the mutation function of migarney information theory.

the?mutation function of migarney information theory as follow ,

(λ.(i->j))=exp{-((∏..N(i->j))((exp{ - (p.N(i->j))}+1)*(n.N(i->j))))}

?(λ.(i->j)) is?probability function that having keep the original feature and having no mutation from state i to state j

(p.N(i->j)) is?transition probability

(n.N(i->j)) is?amount of information

N(i->j) is amount of substate from state i to state j

(λ.(i->j))=exp{-((∏..N(i->j))((exp{ -(A.N(i->j))(p.N(i->j))}+1)*(B.N(i->j))(n.N(i->j))))}

(A.N(i->j)) is the scale of transition probability

(B.N(i->j)) is the scale that amount of information

通過誘導(dǎo)調(diào)頻和同頻共振的技術(shù)可以直接對視覺神經(jīng)模塊進(jìn)行頻率方面的容許通信的組合構(gòu)建和通過migarney信息論中的異變函數(shù)來

對基于可見光譜的頻率進(jìn)行

組合拼接然后形成完整的有顏色的視覺感知圖像,并且無需利用深度神經(jīng)網(wǎng)絡(luò)對視覺皮層進(jìn)行訓(xùn)練,深度神經(jīng)網(wǎng)絡(luò)對視覺皮層的訓(xùn)練速度太慢了,速度最快的就是利用migarney信息論中的異變函數(shù)對可見光譜的頻率進(jìn)行組合拼接然后形成完美的視覺感知圖像。

migarney 信息論中的異變函數(shù)定義

(λ.(i->j))=exp{-((∏..N(i->j))((exp{ - (p.N(i->j))}

+1)*(n.N(i->j))))}

其中 ,?(λ.(i->j))為從狀態(tài)i到狀態(tài)j的狀態(tài)轉(zhuǎn)移的過程中保持原有的特征并且不發(fā)生異變的概率函數(shù)

(p.N(i->j))為轉(zhuǎn)移概率?

(n.N(i->j))為信息量

N(i->j)為從狀態(tài)i到狀態(tài)j的狀態(tài)轉(zhuǎn)移的過程中的子狀態(tài)數(shù)

(λ.(i->j))=exp{-((∏..N(i->j))((exp{ -(A.N(i->j))(p.N(i->j))}+1)*(B.N(i->j))(n.N(i->j))))}

(A.N(i->j))為概率轉(zhuǎn)移標(biāo)度

(B.N(i->j))為信息量標(biāo)度?

the works copyright content and the worker information (作品的版權(quán)內(nèi)容和作者信息):

my English name is :

migarney Pierpont Tesla Morgan Rothschild

my Japanese name is : みがに

my Chinese name is : 劉文宇

address now :

中國福建省福州市長樂區(qū)金峰鎮(zhèn)華劉村

中國福建省福州市長樂區(qū)鶴上鎮(zhèn)洞湖黃朱村

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