data with noise.dat

图像处理的压缩算法

Time	Signal	Response
1	0.34391	1.72365E-26
2	0.55521	1.89511E-24
3	1.0563	1.70592E-22
4	0.97923	1.25726E-20
5	1.38473	7.58635E-19
6	1.52278	3.74784E-17
7	1.76042	1.5159E-15
8	1.96653	5.01997E-14
9	2.12463	1.36105E-12
10	2.56168	3.02125E-11
11	2.32137	5.49086E-10
12	2.47921	8.17025E-9
13	3.02567	9.9534E-8
14	2.90745	9.9277E-7
15	3.13703	8.10713E-6
16	3.4461	5.42034E-5
17	3.21917	2.96707E-4
18	3.41658	0.00133
19	3.46079	0.00488
20	3.64485	0.01466
21	3.49143	0.03605
22	3.76505	0.0726
23	3.82044	0.1197
24	3.96682	0.16158
25	3.78539	0.17857
26	4.06655	0.16158
27	4.0288	0.1197
28	3.86954	0.0726
29	4.17845	0.03605
30	4.03827	0.01466
31	4.26468	0.00488
32	3.93353	0.00133
33	4.0999	2.96707E-4
34	4.02283	5.42034E-5
35	4.24265	8.10713E-6
36	4.41507	9.9277E-7
37	4.26201	9.9534E-8
38	4.19291	8.17025E-9
39	4.00358	5.49086E-10
40	4.07897	3.02125E-11
41	3.99777	1.36105E-12
42	4.12686	5.01997E-14
43	4.18332	1.5159E-15
44	4.22089	3.74784E-17
45	4.18232	7.58635E-19
46	3.96459	1.25726E-20
47	3.87041	1.70592E-22
48	4.13135	1.89511E-24
49	3.74754	1.72365E-26
50	3.90509	1.28353E-28
51	3.72507	7.82537E-31
52	3.63108	
53	3.49716	
54	3.36457	
55	3.48058	
56	3.38849	
57	3.34831	
58	3.19094	
59	3.55074	
60	3.28588	
61	3.19216	
62	2.96482	
63	2.92033	
64	2.79861	
65	3.08803	
66	3.10087	
67	2.93939	
68	2.65003	
69	2.68828	
70	2.46596	
71	2.70485	
72	2.37245	
73	2.59517	
74	2.14932	
75	2.51752	
76	2.47803	
77	2.34114	
78	2.21628	
79	1.87252	
80	2.01065	
81	2.12977	
82	1.95813	
83	1.99275	
84	1.90798	
85	1.72366	
86	1.42072	
87	1.61575	
88	1.76219	
89	1.23855	
90	1.38445	
91	1.39887	
92	1.46022	
93	1.08256	
94	1.30475	
95	1.13774	
96	1.09224	
97	1.06493	
98	0.85345	
99	0.88173	
100	1.12046	
101	1.1194	
102	0.79074	
103	0.65181	
104	0.7957	
105	0.58149	
106	0.50235	
107	0.65725	
108	0.71842	
109	0.38825	
110	0.63373	
111	0.5169	
112	0.55498	
113	0.50813	
114	0.46815	
115	0.44979	
116	0.40705	
117	0.41919	
118	0.38701	
119	0.20901	
120	0.16365	
121	0.07369	
122	0.45465	
123	0.08222	
124	0.39008	
125	0.29526	
126	-0.08233	
127	0.24849	
128	-0.11674	
129	0.27618	
130	-0.02425	
131	0.14532	
132	0.21514	
133	-0.14364	
134	0.09573	
135	0.09774	
136	0.19344	
137	-0.04307	
138	-0.0758	
139	-0.06329	
140	-0.00698	
141	-0.06379	
142	-0.09326	
143	0.12235	
144	-0.2032	
145	-0.12319	
146	-0.29798	
147	-0.09267	
148	-0.24221	
149	-0.06468	
150	-0.0685	
151	-0.20007	
152	0.04327	
153	-0.2722	
154	-0.03844	
155	-0.20816	
156	-0.27723	
157	0.14133	
158	0.01095	
159	0.09805	
160	-0.13246	
161	-0.17043	
162	0.11434	
163	-0.15246	
164	-0.13086	
165	-0.26807	
166	0.13148	
167	-0.17878	
168	0.05231	
169	-0.30992	
170	-0.15228	
171	-0.26189	
172	-0.21763	
173	-0.08338	
174	-0.27338	
175	0.14282	
176	-0.27455	
177	0.14308	
178	0.17765	
179	-0.07642	
180	0.09795	
181	0.07027	
182	-0.14017	
183	-0.1052	
184	0.08011	
185	0.09372	
186	-0.16317	
187	0.17582	
188	0.11933	
189	-0.11904	
190	0.25948	
191	-0.15182	
192	-0.03013	
193	0.10909	
194	-0.05942	
195	0.17999	
196	0.11617	
197	-0.02937	
198	-0.05482	
199	0.0787	
200	0.07246	
201	0.26003	
202	0.15837	
203	0.1715	
204	0.2172	
205	-0.0291	
206	0.33098	
207	0.36407	
208	0.11246	
209	0.03573	
210	0.0372	
211	0.38558	
212	-0.00545	
213	0.18663	
214	0.35659	
215	0.02324	
216	0.07684	
217	0.39387	
218	0.18161	
219	-0.04361	
220	0.03769	
221	0.19876	
222	0.26034	
223	0.33033	
224	-0.03723	
225	0.03883	
226	0.45	
227	0.06679	
228	0.04565	
229	0.10669	
230	0.22476	
231	0.09731	
232	0.11315	
233	0.28347	
234	-0.01043	
235	0.26625	
236	0.0389	
237	0.19915	
238	0.11979	
239	0.23406