Update README.md

Author: LRQ577

README.md

@@ -1,7 +1,7 @@
 # FAITH :Frequency-domain Attention In Two Horizon for TSF
-# Soon...
 
-Time series forecasting is a critical demand for real applications. Enlighted by the classic time series analysis and stochastic process theory, we propose the Autoformer as a general series forecasting model [paper](https://arxiv.org/pdf/2405.13300) .
+
+Time series forecasting is a critical demand for real applications. Enlighted by the classic time series analysis and stochastic process theory, we propose the FAITH as a general series forecasting model [paper](https://arxiv.org/pdf/2405.13300) .
 
 FAITH  captures inter-channel relationships and temporal global information in the sequence. Extensive experiments on 6 benchmarks for long-term forecasting and 5 benchmarks for short-term forecasting demonstrate that FAITH outperforms existing models in many fields, such as electricity, weather and traffic, proving its effectiveness and superiority both in long-term and short-term time series forecasting tasks.
 
@@ -10,11 +10,14 @@ FAITH  captures inter-channel relationships and temporal global information in t
 ![fig22](https://github.com/LRQ577/FAITH/assets/119293404/5844097a-ef86-4c25-bb45-c31fbfa15c2d)
 
 # FCTEM of FAITH
-![fig44](https://github.com/LRQ577/FAITH/assets/119293404/e85c13a9-bd95-4ec9-932d-a77036c33000)
+![fig44](https://github.com/user-attachments/assets/ffc74c52-5edc-421d-b162-25e2c5205b24)
 
 # Experiment
-![image](https://github.com/LRQ577/FAITH/assets/119293404/bb514b27-3099-4347-993e-ae6d1c797455)
+![image](https://github.com/user-attachments/assets/ac23ab86-7879-4b3b-bea4-445e67c10e35)
+
+![image](https://github.com/user-attachments/assets/639bb785-ad70-40c0-99b1-2ff5d9e9d92c)
 
+![image](https://github.com/user-attachments/assets/ff6fd590-45c2-4587-9ac3-477522881505)
 
 # Start
 1. ```pip install -r requirement.txt ```
@@ -26,7 +29,7 @@ FAITH  captures inter-channel relationships and temporal global information in t
 
 
 # Contact 
-If you have any questions, please contact liruiqi1@sia.cn. Welcome to discuss together.
+If you have any questions, please contact 1284042551@qq.com. Welcome to discuss together.
 
 # Citation
 If you find this repo useful, please cite our paper