當(dāng)前位置：首頁(yè) > 编程资源 > 编程问答 >内容正文

编程问答

卷积核一定可以提升网络性能吗？-分类0，2

發(fā)布時(shí)間：2025/4/5 编程问答 35 豆豆

生活随笔收集整理的這篇文章主要介紹了卷积核一定可以提升网络性能吗？-分类0，2 小編覺得挺不錯(cuò)的,現(xiàn)在分享給大家,幫大家做個(gè)參考.

制作一個(gè)網(wǎng)絡(luò)然后向這個(gè)網(wǎng)絡(luò)上加1-9個(gè)卷積核，通過網(wǎng)絡(luò)的分辨準(zhǔn)確率來比較卷積核對(duì)網(wǎng)絡(luò)性能的影響。

網(wǎng)絡(luò)的結(jié)構(gòu)是

(mnist 0 ,mnist2)81-con(3*3)*n-(49*n)-30-2-(1,0) || (0,1)

分類mnist的0和2，將28*28的圖片壓縮到9*9，向這個(gè)網(wǎng)絡(luò)增加n個(gè)3*3的卷積核，網(wǎng)絡(luò)隱藏層的節(jié)點(diǎn)數(shù)是30個(gè)，讓0向（1，0）收斂，讓2向（0，1）收斂。讓n分別等于0-9.當(dāng)n=0時(shí)，網(wǎng)絡(luò)相當(dāng)于一個(gè)三層的網(wǎng)絡(luò)

(mnist 0 ,mnist2)81-30-2-(1,0) || (0,1)

用這個(gè)沒有卷積核的3層網(wǎng)絡(luò)作為參照比較網(wǎng)絡(luò)性能的變化。

網(wǎng)絡(luò)迭代的停止標(biāo)準(zhǔn)是：

|網(wǎng)絡(luò)的輸出值-目標(biāo)函數(shù)|<δ,

讓?duì)姆謩e等于0.5到1e-6的34個(gè)值每個(gè)δ收斂199次，通過每次收斂的準(zhǔn)確率的平均值和199次收斂的最大值來比較性能的變化。一共收斂了9*34*199次。

平均性能的表格

?	?	1	2	3	4	5	6	7	8	9
δ	平均準(zhǔn)確率p-ave	平均準(zhǔn)確率p-ave	平均準(zhǔn)確率p-ave	平均準(zhǔn)確率p-ave	平均準(zhǔn)確率p-ave	平均準(zhǔn)確率p-ave	平均準(zhǔn)確率p-ave	平均準(zhǔn)確率p-ave	平均準(zhǔn)確率p-ave	平均準(zhǔn)確率p-ave
0.5	0.5523392	0.5039786	0.502023	0.5121532	0.5091611	0.5093609	0.5166738	0.5169935	0.5132447	0.5188143
0.4	0.9516094	0.7559143	0.7354191	0.7508267	0.6995165	0.6534412	0.6503317	0.6558139	0.6173537	0.649505
0.3	0.9548188	0.8792771	0.8562769	0.8324675	0.8165954	0.7935727	0.7344676	0.7343227	0.7617811	0.7652077
0.2	0.9455553	0.9126847	0.8743069	0.8599209	0.8596436	0.8487367	0.8041924	0.7903484	0.7557494	0.7660594
0.1	0.9601137	0.9143681	0.8736151	0.8528228	0.8806283	0.8796717	0.8396106	0.7770588	0.7376894	0.6889642
0.01	0.9393064	0.9245307	0.8586921	0.7835649	0.7043043	0.7821613	0.8381045	0.8263509	0.8017723	0.7628475
0.001	0.9764878	0.9358697	0.9156918	0.7677628	0.677308	0.6918139	0.6827552	0.6992168	0.6397644	0.6579093
9.00E-04	0.976268	0.9418714	0.9082715	0.7771262	0.6896435	0.6739163	0.6619629	0.6649675	0.6600498	0.6836219
8.00E-04	0.9763554	0.9388343	0.9299529	0.7895916	0.6767286	0.6480064	0.6607965	0.6492677	0.6606017	0.686042
7.00E-04	0.9764379	0.937663	0.9266137	0.8038253	0.7073439	0.6674051	0.6691085	0.6738489	0.6938295	0.748409
6.00E-04	0.9775193	0.9359047	0.9417115	0.842268	0.7357039	0.6842812	0.6739413	0.686047	0.7140099	0.772683
5.00E-04	0.9785883	0.9323032	0.9336768	0.8814125	0.7663092	0.7402345	0.7195346	0.761384	0.795848	0.8459095
4.00E-04	0.9786957	0.9397759	0.9376979	0.9120353	0.8389612	0.8006309	0.7972392	0.8230716	0.8615768	0.8792496
3.00E-04	0.9787057	0.9376355	0.9369512	0.9286942	0.8930937	0.8779609	0.8737425	0.9023822	0.9043228	0.9192658
2.00E-04	0.9807637	0.9394288	0.9160514	0.9294584	0.9271831	0.9271157	0.9328826	0.9386095	0.9462971	0.9588349
1.00E-04	0.980931	0.9435847	0.9207244	0.9284419	0.9477307	0.9556655	0.9600662	0.9628136	0.9671569	0.970661
9.00E-05	0.980409	0.9463745	0.9198777	0.9400207	0.949439	0.9538298	0.9648616	0.961882	0.9693647	0.9697219
8.00E-05	0.9805963	0.9482127	0.9346559	0.9425932	0.9509601	0.9606856	0.9629584	0.9673242	0.968031	0.9698842
7.00E-05	0.9805189	0.9511449	0.9402679	0.9501708	0.957721	0.9614924	0.9692398	0.9690101	0.9715276	0.9699816
6.00E-05	0.9813631	0.9534327	0.9404153	0.9503007	0.962876	0.9671019	0.9707534	0.9715576	0.9721071	0.9730986
5.00E-05	0.9820649	0.9538448	0.9515645	0.9591546	0.9651638	0.9709657	0.9717874	0.973698	0.9731785	0.9733808
4.00E-05	0.9827467	0.953645	0.9557554	0.9651563	0.9691499	0.9737555	0.9740926	0.9746471	0.9739852	0.975219
3.00E-05	0.9830564	0.9588249	0.964387	0.9707584	0.9724492	0.9763055	0.9759883	0.9759009	0.9736655	0.9752915
2.00E-05	0.983526	0.9624015	0.9721995	0.9748769	0.975776	0.9766801	0.9769274	0.9769873	0.9756062	0.9740602
1.00E-05	0.9821723	0.9718698	0.9794749	0.977799	0.9770598	0.9779814	0.9764878	0.9773944	0.9761531	0.974707
9.00E-06	0.9822897	0.9740377	0.9801942	0.9780488	0.9786107	0.9772221	0.9770198	0.9759833	0.9749343	0.9747445
8.00E-06	0.9825819	0.9755562	0.978888	0.9779913	0.9770023	0.9771671	0.9770847	0.9765203	0.9760507	0.9765053
7.00E-06	0.9826743	0.9759308	0.9779514	0.9788755	0.9774069	0.9771871	0.9777766	0.9768724	0.977859	0.9755887
6.00E-06	0.9826368	0.9772346	0.9790528	0.9789454	0.9779214	0.9770747	0.9771497	0.9769199	0.9764478	0.9761681
5.00E-06	0.9826618	0.9778415	0.9786532	0.9784184	0.9771247	0.978346	0.9778215	0.9772096	0.9766701	0.9759308
4.00E-06	0.9829016	0.9796822	0.9805738	0.9779464	0.9781812	0.9785108	0.9785833	0.9789554	0.9774369	0.9764828
3.00E-06	0.9834086	0.9801243	0.9796522	0.9786957	0.9785083	0.9790953	0.979405	0.9794799	0.9787356	0.9779764
2.00E-06	0.9839805	0.9801667	0.9800768	0.9799894	0.9800469	0.9802292	0.9806188	0.9806488	0.9797047	0.9782211
1.00E-06	0.9850945	0.9819625	0.9821623	0.9810084	0.9816928	0.9825095	0.98199	0.9821398	0.9816953	0.9817527

沒有加卷積核的3層網(wǎng)絡(luò)的平均準(zhǔn)確率大于任何加卷積核的網(wǎng)絡(luò)，也就是增加卷積核對(duì)這個(gè)網(wǎng)絡(luò)的平均性能沒有任何正面價(jià)值。平均性能隨卷積核變化的一個(gè)大致的規(guī)律，有2個(gè)卷積核的網(wǎng)絡(luò)的平均性能最大，當(dāng)卷積核數(shù)量超過2個(gè)以后隨著卷積核數(shù)量的增加網(wǎng)絡(luò)的平均性能有明顯的下降趨勢(shì)。

按照平均性能排序如下

81*30*2>2>3>4>5>6>7>8>9>1

再比較網(wǎng)絡(luò)的最大性能的變化

?	?	1	2	3	4	5	6	7	8	9
δ	最大值p-max	最大值p-max	最大值p-max	最大值p-max	最大值p-max	最大值p-max	最大值p-max	最大值p-max	最大值p-max	最大值p-max
0.5	0.9284294	0.8489066	0.7897614	0.7659046	0.7997018	0.888171	0.8533797	0.833499	0.8136183	0.8210736
0.4	0.9671968	0.97167	0.9771372	0.972664	0.972664	0.9741551	0.9741551	0.9741551	0.9761431	0.9736581
0.3	0.9686879	0.971173	0.972664	0.972167	0.9681909	0.973161	0.97167	0.9686879	0.973161	0.973161
0.2	0.9627237	0.9756461	0.971173	0.9741551	0.9736581	0.9746521	0.9736581	0.972664	0.9736581	0.97167
0.1	0.9706759	0.9691849	0.9786282	0.97167	0.9761431	0.9766402	0.9756461	0.9756461	0.9681909	0.9671968
0.01	0.9776342	0.9751491	0.9761431	0.9776342	0.9761431	0.9706759	0.972167	0.9756461	0.9736581	0.972167
0.001	0.9816103	0.9796223	0.9801193	0.9741551	0.9776342	0.9786282	0.9791252	0.9826044	0.9806163	0.9801193
9.00E-04	0.9806163	0.9786282	0.9791252	0.9751491	0.9771372	0.9781312	0.9811133	0.9806163	0.9806163	0.9791252
8.00E-04	0.9816103	0.9796223	0.9811133	0.9791252	0.9746521	0.9801193	0.9786282	0.9806163	0.9806163	0.9816103
7.00E-04	0.9816103	0.9811133	0.9786282	0.9781312	0.9796223	0.9771372	0.9781312	0.9796223	0.9801193	0.9831014
6.00E-04	0.9816103	0.9791252	0.9806163	0.9796223	0.9771372	0.9781312	0.972167	0.9791252	0.9806163	0.9801193
5.00E-04	0.9816103	0.9791252	0.9811133	0.9811133	0.9811133	0.9796223	0.9776342	0.9816103	0.9831014	0.9845924
4.00E-04	0.9831014	0.9811133	0.9791252	0.9801193	0.9796223	0.9811133	0.9791252	0.9816103	0.9826044	0.9840954
3.00E-04	0.9835984	0.9786282	0.9826044	0.9811133	0.9806163	0.9835984	0.9831014	0.9821074	0.9840954	0.9845924
2.00E-04	0.9831014	0.9845924	0.9840954	0.9811133	0.9831014	0.9855865	0.9850895	0.9850895	0.9865805	0.9860835
1.00E-04	0.9831014	0.9835984	0.9835984	0.9840954	0.9845924	0.9865805	0.9860835	0.9875746	0.9875746	0.9880716
9.00E-05	0.9845924	0.9816103	0.9826044	0.9860835	0.9860835	0.9860835	0.9870775	0.9875746	0.9865805	0.9875746
8.00E-05	0.9845924	0.9835984	0.9845924	0.9855865	0.9865805	0.9870775	0.9870775	0.9875746	0.9860835	0.9865805
7.00E-05	0.9845924	0.9821074	0.9831014	0.9855865	0.9865805	0.9875746	0.9875746	0.9870775	0.9870775	0.9875746
6.00E-05	0.9845924	0.9835984	0.9845924	0.9855865	0.9870775	0.9865805	0.9875746	0.9880716	0.9865805	0.9875746
5.00E-05	0.9850895	0.9826044	0.9855865	0.9865805	0.9880716	0.9875746	0.9895626	0.9875746	0.9875746	0.9870775
4.00E-05	0.9850895	0.9826044	0.9855865	0.9875746	0.9885686	0.9875746	0.9880716	0.9890656	0.9875746	0.9875746
3.00E-05	0.9855865	0.9885686	0.9880716	0.9875746	0.9880716	0.9880716	0.9880716	0.9885686	0.9880716	0.9880716
2.00E-05	0.9855865	0.9880716	0.9875746	0.9875746	0.9900596	0.9875746	0.9875746	0.9890656	0.9890656	0.9885686
1.00E-05	0.9855865	0.9875746	0.9880716	0.9895626	0.9875746	0.9885686	0.9885686	0.9895626	0.9890656	0.9885686
9.00E-06	0.9850895	0.9870775	0.9885686	0.9880716	0.9885686	0.9890656	0.9885686	0.9885686	0.9895626	0.9885686
8.00E-06	0.9850895	0.9865805	0.9875746	0.9885686	0.9895626	0.9885686	0.9885686	0.9885686	0.9890656	0.9890656
7.00E-06	0.9845924	0.9875746	0.9885686	0.9880716	0.9885686	0.9880716	0.9885686	0.9880716	0.9880716	0.9885686
6.00E-06	0.9845924	0.9880716	0.9885686	0.9885686	0.9880716	0.9880716	0.9885686	0.9885686	0.9885686	0.9900596
5.00E-06	0.9845924	0.9875746	0.9880716	0.9895626	0.9890656	0.9880716	0.9900596	0.9890656	0.9885686	0.9885686
4.00E-06	0.9845924	0.9880716	0.9885686	0.9890656	0.9890656	0.9880716	0.9895626	0.9895626	0.9885686	0.9885686
3.00E-06	0.9855865	0.9875746	0.9880716	0.9890656	0.9880716	0.9885686	0.9895626	0.9880716	0.9890656	0.9900596
2.00E-06	0.9870775	0.9875746	0.9885686	0.9890656	0.9885686	0.9890656	0.9885686	0.9895626	0.9875746	0.9890656
1.00E-06	0.9875746	0.9890656	0.9900596	0.9905567	0.9895626	0.9915507	0.9885686	0.9895626	0.9895626	0.9890656

雖然增加卷積核對(duì)網(wǎng)路的平均性能沒有正面價(jià)值，但有卷積核網(wǎng)絡(luò)的最大性能都好于原始的3層網(wǎng)絡(luò)，表明卷積核對(duì)網(wǎng)絡(luò)的最大性能有顯著提升。

用收斂標(biāo)準(zhǔn)=1e-6的值排序

5>3>2>4=7=8>1=9>6>81*30*2

加上前面做的0-1，0-5，0-6的實(shí)驗(yàn)已經(jīng)做了4組，將所有的數(shù)據(jù)總結(jié)成表格

平均性能	0-1	81302>2>3>4>5>6>7>8>9>1			沒有正面價(jià)值
?	0-5	2>3>4>5>6>7>8>9>81-30-2>1			明顯提升
?	0-6	81302>2>9>8>1>7>6>5>4>3			沒有正面價(jià)值
?	0-2	81302>2>3>4>5>6>7>8>9>1			沒有正面價(jià)值
?	?	?	?	?	?
最大性能	0-1	81302=1=2=3=4=5=6=7=8=9			沒有提升
?	0-5	2>3>4>5>6>7>8>9>1>81-30-2			提升明顯
?	0-6	81302=2=7>8>1=3=4>6>5			無明顯提升
?	0-2	5>3>2>4=7=8>1=9>6>81302			提升明顯

對(duì)網(wǎng)絡(luò)平均性能有提升的只有0-5，對(duì)網(wǎng)絡(luò)最大性能有明顯提升的只有0-5和0-2.而對(duì)于0-1和0-6.增加卷積核對(duì)網(wǎng)絡(luò)的平均性能和最大性能都沒有任何正面價(jià)值。表明卷積核對(duì)網(wǎng)絡(luò)性能的影響不是絕對(duì)的，與測(cè)試集有很大的關(guān)系。并不是所有的測(cè)試集都適于加卷積核。

比較迭代次數(shù)

?	?	1	2	3	4	5	6	7	8	9
δ	迭代次數(shù)n	迭代次數(shù)n	迭代次數(shù)n	迭代次數(shù)n	迭代次數(shù)n	迭代次數(shù)n	迭代次數(shù)n	迭代次數(shù)n	迭代次數(shù)n	迭代次數(shù)n
0.5	8.8643216	16.246231	13.809045	14.904523	15.175879	12.135678	11.834171	11.924623	13.065327	11.130653
0.4	208.9397	1685.9246	1134.1307	882.45729	751.93467	664.0804	594.83417	526.31658	481.18593	445.8191
0.3	268.72864	1923.0955	1299.8291	1047.608	869.26633	788.86935	699.34171	648.02513	593.94472	548.1809
0.2	324.01508	2120.0452	1440.6281	1160.9749	988.66332	872.42714	790.13568	712.67839	664.07538	630.42211
0.1	410.58794	2318.6683	1637.1307	1291.804	1105.392	971.68342	880.61307	814.58794	764.27136	718.45729
0.01	685.54774	2832.7236	2076.397	1656.4171	1424.8995	1282.6281	1206.7035	1101.2513	1039.4724	999.18593
0.001	1447.1307	3803.3216	2899.7387	2436.8945	2234.598	2142.9648	2086.7085	2070.9849	2123.7638	2199.7889
9.00E-04	1450.9146	3783.5276	2924.2462	2495.8342	2291.7538	2173.5628	2137.2211	2139.3467	2256.804	2365.5226
8.00E-04	1494.9246	3831.3266	3005.1759	2545.6231	2314.8342	2233.1558	2231.5327	2247.4975	2312.9698	2508.6784
7.00E-04	1552.7136	3962.8894	3032.8241	2621.9497	2432.1558	2312.2362	2360.9447	2437.2261	2532.6633	3025.8291
6.00E-04	1711.6281	4070.799	3151.9698	2738.2462	2520.1809	2427.5578	2559.2161	2598.5427	2897.8191	3426.1709
5.00E-04	1968.7136	4228.1005	3268.7487	2908.4422	2656.392	2614.2312	2638.9397	3189.1759	3705.1457	4812.1407
4.00E-04	2165.0553	4379.6533	3413.5879	3049.1709	2878.2161	2938.7839	3379.3819	4073.3719	5242.4171	7248.4221
3.00E-04	2324.0804	4616.3869	3568.7487	3236.6734	3262.6985	3474.1357	4279.6533	6453.8191	8586.4523	11609.673
2.00E-04	2720.8442	5050.8744	4034.0854	3941.7839	4741.608	5935.9347	8696.7739	11151.116	15180.141	19449.472
1.00E-04	3165.7085	6349.6985	5698.9447	6692.2211	9883.7035	14487.849	20128.899	26472.593	31021.317	34488.161
9.00E-05	3407.9095	6705.2513	6425.6432	7671.8342	10057.864	16786.427	22643.764	27280.819	33107.07	36141.161
8.00E-05	3486.7638	6955.8141	6875.5779	8632.7638	13695.608	18656.789	24313.794	30661.899	32898.834	37901.487
7.00E-05	3668.6834	7528.9196	7582.6533	10520.673	14594.503	21585.935	27430.905	33478.191	37926.065	39971.744
6.00E-05	3962.5628	8184.2915	8908.6583	10364.412	17772.01	26005.452	33621.568	37461.166	40297.015	43397.05
5.00E-05	4167.6784	8865.0201	9484.1759	13928.859	20620.387	29064.899	36309.246	40110.719	43048.417	45538.367
4.00E-05	4515.8291	9644.5578	11563.161	18354.367	27010.352	33951.97	40799.658	44108.271	45917.915	48308.945
3.00E-05	5059.8794	11485.899	15935.819	23537.467	31983.07	40540.769	44894.171	48028.648	49944.307	52696.226
2.00E-05	6524.8744	15515.141	23050.367	31693.899	39692.101	46629.558	50373.94	54465.653	55854.437	57249.005
1.00E-05	8527.8995	25127.07	34262.568	43816.402	51902.055	55930.221	60159.965	61394.462	63830.06	66139.307
9.00E-06	8746.4221	26410.513	37680.035	46022.296	54010.824	57544.231	61327.05	63699.201	64750.774	68351
8.00E-06	9474.0101	29507.945	39589.829	48614.332	54025.236	59733.015	62842.513	64384.889	66818.925	68970.196
7.00E-06	10301.668	31298.121	40019.106	50429.01	56361.678	62009	63321.663	66217.427	69258.372	69606.422
6.00E-06	11850.653	33845.357	44199.276	51939.93	59028.905	63013.839	65983.749	67526.186	69809.583	70851.06
5.00E-06	13068.734	36965.256	47009.317	56133.382	62123.925	66072.719	68282.146	71326.035	72951.161	74612.08
4.00E-06	14670.05	40347.784	49610.824	59106.07	63852.477	69004.804	71463.156	73956.101	77287.442	76819.804
3.00E-06	17112.472	44845.005	56031.894	62566.347	67823.025	73042.563	74778.497	77379.653	80787.312	81893.528
2.00E-06	23285.869	52058.754	62225.432	70379.01	74180.412	77512.573	81224.447	85341.327	87238.95	87805.156
1.00E-06	35222.241	66830.714	77563.397	82040.663	86059.04	90214.985	93471.638	96062.583	99403.251	102968.42

迭代次數(shù)隨著卷積核數(shù)量的增加而增加，在《計(jì)算多卷積核神經(jīng)網(wǎng)絡(luò)迭代次數(shù)》中已經(jīng)得到的卷積核的數(shù)量與迭代次數(shù)的公式

ni/n(i-1)	?	b	1.1605951	1.057724	1.0489803	1.0482918	1.0360988	1.027719	1.034776	1.0358657
(i/(i-1))**0.5		a	1.4142136	1.2247449	1.1547005	1.118034	1.0954451	1.0801234	1.069045	1.0606602
?	?	?	?	?	?	?	?	?	?	?
a/b	α	?	1.2185245	1.157906	1.1007838	1.0665294	1.0572786	1.050991	1.0331173	1.023936
?	X	?	2	3	4	5	6	7	8	9

用α和x擬合方程

α=1.3075677654798437*x**-0.11553016292685217

0.9715966417109875?? ******? 決定系數(shù) r**2

計(jì)算迭代次數(shù)

?	2	3	4	5	6	7	8	9
α	1.2069413	1.1517078	1.1140588	1.0857056	1.0630759	1.0443111	1.0283242	1.0144261
∏α	?	1.1517078	1.2830702	1.3930366	1.4809036	1.546524	1.5903281	1.6132704
?	?	?	?	?	?	?	?	?
計(jì)算	?	82482.182	85491.196	88036.813	90717.416	93828.37	97543.891	101989.61
實(shí)測(cè)	?	82040.663	86059.04	90214.985	93471.638	96062.583	99403.251	102968.42
誤差	?	0.0053817	0.0065983	0.0241442	0.0294659	0.0232579	0.0187052	0.0095059

比較耗時(shí)

?	?	1	2	3	4	5	6	7	8	9
δ	耗時(shí) min/199	耗時(shí) min/199	耗時(shí) min/199	耗時(shí) min/199	耗時(shí) min/199	耗時(shí) min/199	耗時(shí) min/199	耗時(shí) min/199	耗時(shí) min/199	耗時(shí) min/199
0.5	0.06415	0.1054333	0.1807833	0.2866167	0.3691167	0.4632	0.6012167	0.68235	0.7749	0.8857667
0.4	0.0743	0.4034333	0.5565167	0.74555	0.8677	1.0177333	1.2258	1.317	1.4365333	1.5769833
0.3	0.0762833	0.4464333	0.6118	0.8334833	0.9509833	1.1233167	1.3131	1.4768	1.5941	1.7541667
0.2	0.08025	0.4785167	0.66015	0.88305	1.0305833	1.1935333	1.3994	1.49935	1.6984167	1.8722667
0.1	0.0854667	0.5151333	0.7269333	0.9404167	1.1488	1.2794167	1.4967	0.6726667	1.81285	2.0303667
0.01	0.10295	0.6091	0.8742833	1.1268833	1.3877833	1.5445667	1.87975	1.98915	2.1972667	2.4928833
0.001	0.1482167	0.7868167	1.1538	1.5269333	1.9254333	2.2772667	2.8063167	3.1866833	3.7478167	4.4037333
9.00E-04	0.1486833	0.7794833	1.16055	1.5606167	1.969	2.3014333	2.8294333	3.2884667	3.9535667	1.89435
8.00E-04	0.1523833	0.7895	1.1887833	1.58825	1.9530167	2.3543833	2.89775	3.4075167	3.9764333	4.8350333
7.00E-04	0.15595	0.8114	1.1984167	1.62435	2.0165333	2.4227167	3.0292167	3.6387333	4.3147167	5.7025833
6.00E-04	0.1680833	0.8324333	1.2386	1.6883667	2.0880667	2.5167	3.18455	3.8301	4.8615833	6.2168833
5.00E-04	0.1823667	0.8596	1.2762667	1.7719167	2.1733333	2.6760833	3.2791167	4.5327833	6.0158667	8.5344833
4.00E-04	0.1947833	0.8926833	1.3244833	1.8532833	0.6664	2.9511333	4.0198333	5.58965	8.1587833	12.120433
3.00E-04	0.2015833	0.9296333	1.3770167	1.9949667	2.5713	3.3963333	4.93535	8.5260333	12.716067	18.7017
2.00E-04	0.2242667	1.07535	1.5356333	2.4373833	3.6019667	5.4545	7.9383167	14.16995	21.765317	29.262633
1.00E-04	0.2510167	1.3040167	2.0991	3.9648333	7.1169	12.690533	20.795567	31.041767	43.3882	54.798383
9.00E-05	0.2691833	1.3718833	2.3460667	4.2682	7.1659667	14.644033	23.287683	34.210233	46.565233	54.359333
8.00E-05	0.2690667	1.41815	2.4975833	4.7310667	9.6323167	16.210883	24.950917	35.979533	46.18115	59.05395
7.00E-05	0.2797	1.5245333	2.73555	5.70455	10.233417	18.691283	28.08415	40.165217	53.254283	62.658783
6.00E-05	0.29395	1.64815	3.18345	5.6891333	12.394317	22.412517	34.39305	43.790267	56.792533	66.610467
5.00E-05	0.3057167	0.7482667	3.3784667	7.4962667	14.319367	25.002167	38.500217	48.504167	58.532967	71.23395
4.00E-05	0.32555	1.90655	4.0798	8.5269167	18.6522	29.133117	41.577167	52.877717	63.498467	74.2049
3.00E-05	0.3573333	2.2570667	5.5666667	12.17225	22.0143	34.778783	45.4032	57.217	68.8245	83.56915
2.00E-05	0.4487167	2.9843667	7.9680833	16.277983	25.902283	40.653083	50.3917	67.005917	76.049067	87.9441
1.00E-05	0.5657	4.6324	12.738767	22.3845	35.64345	48.739217	61.586	70.405867	87.764633	101.07163
9.00E-06	0.5779	4.8042167	13.97685	23.499033	37.245083	48.107167	61.408567	75.853533	89.590633	106.89732
8.00E-06	0.6237333	5.3426	13.776983	24.87535	35.31665	50.382933	64.300433	77.051283	91.333683	105.29282
7.00E-06	0.6701667	5.6624333	11.376483	26.492033	38.42935	53.487317	64.339583	78.093217	96.4085	107.67667
6.00E-06	-1.043133	6.1118333	15.4332	27.433567	40.1873	52.854733	67.0226	79.72825	94.623517	109.36867
5.00E-06	0.8278667	6.6677333	16.386617	27.391317	42.329833	57.257867	69.3746	84.96685	100.74403	115.31163
4.00E-06	0.92955	7.2674	17.24095	30.8037	46.6526	57.598467	74.86045	88.066183	106.69952	118.55075
3.00E-06	1.0805333	8.0748	19.4551	32.2475	44.217	62.321083	78.466417	92.807433	112.71635	126.68888
2.00E-06	1.4429333	9.3541	22.58695	38.047467	52.679083	66.735667	82.635983	100.66913	121.80912	135.0271
1.00E-06	2.15025	11.933783	24.124117	40.834483	57.550183	77.955	97.3552	113.19602	138.3318	158.15827

計(jì)算迭代時(shí)間的表達(dá)式

用同樣的辦法

α=1.3075677654798437x*-0.11553016292685217	?	?	?	?	?	?	?	?
?	2	3	4	5	6	7	8	9
α	1.2069413	1.1517078	1.1140588	1.0857056	1.0630759	1.0443111	1.0283242	1.0144261
∏α	?	1.1517078	1.2830702	1.3930366	1.4809036	1.546524	1.5903281	1.6132704
?	?	?	?	?	?	?	?	?
計(jì)算	?	38.480969	53.179713	68.454014	84.646016	102.14023	121.35416	142.7457
實(shí)測(cè)	?	40.834483	57.550183	77.955	97.3552	113.19602	138.3318	158.15827
誤差	?	0.0576355	0.0759419	0.1218778	0.1305445	0.0976694	0.1227313	0.0974503

綜合上面的4個(gè)表格

卷積核并不是對(duì)所有的訓(xùn)練集都有正面價(jià)值，并不是所有的網(wǎng)絡(luò)都可以通過增加卷積核的辦法提升網(wǎng)絡(luò)性能。

《新程序員》：云原生和全面數(shù)字化實(shí)踐50位技術(shù)專家共同創(chuàng)作，文字、視頻、音頻交互閱讀

總結(jié)

以上是生活随笔為你收集整理的卷积核一定可以提升网络性能吗？-分类0，2的全部?jī)?nèi)容，希望文章能夠幫你解決所遇到的問題。

如果覺得生活随笔網(wǎng)站內(nèi)容還不錯(cuò)，歡迎將生活随笔推薦給好友。

上一篇：二分类神经网络的特征光谱---1-2至1
下一篇：江淮骏铃A8120马力多少钱？